Risk Management

August 14 2023

Cybersecurity and the Metaverse: Risks, Threats, Challenges, and Opportunities

Raphael Iloh Artificial Intelligence, Business Continuity, Business Strategy, Cyber Security, Cybersecurity Governance, Infosec, Leadership, Metaverse, Risk Assessment, Risk Management, Security Architecture, Security Risks, Security Strategy artificial intelligence, business agility, business continuity, Business Strategy, Competitive Advantage, compliance, Cyber Security, cybersecurity, data protection, governance, infosecurity, innovation, leadership, Metaverse, privacy, risk management, Security Risks, security strategy, third party risk management

The metaverse, a boundless realm where the lines between the real and the virtual blur into a kaleidoscope of possibilities. The metaverse is a term that describes a 3D virtual world that integrates physical and digital realities as well as enables immersive and interactive experiences for users. Imagine being able to visit any place, meet any person, or do any activity in a realistic and engaging way, without leaving your home.

In this digital utopia, businesses and organizations across various sectors (including retail, finance, education, healthcare, and defence) are embarking on an extraordinary journey. That is the vision of the metaverse, which is expected to experience exponential growth following the ongoing huge improvements and strides in Generative Artificial Intelligence (AI). According to the Wall Street Journal (WSJ), metaverse spending is projected to reach US$5 trillion by 2030 i.e., within the next 7 years.

However, as we delve deeper into the wonders of the metaverse, we must tread with caution and embrace cybersecurity to safeguard this new frontier. In a couple of previous posts, we discussed Artificial Intelligence (AI) in healthcare services. In this article, we’ll discuss some of the main cybersecurity challenges and risks that the metaverse poses to organizations and how they can be effectively addressed. We’ll also discuss some of the opportunities that the metaverse offers to organizations and how they can leverage them to gain a competitive edge.

Understanding the Metaverse: Unravelling the Infinite

The metaverse, a concept once confined to science fiction, is now a reality, rapidly evolving through the convergence of virtual reality, augmented reality, blockchain, the Internet of Things (IoT), and the power of Generative AI. These technologies enable the creation of realistic and dynamic virtual environments that can be accessed by millions of users simultaneously.

This immersive domain transcends the limits of screens and keyboards, presenting an entirely new interface between humans and information. In the retail sector, fashion retailers allow customers to try on virtual outfits, providing a personalized shopping experience like never before. Financial institutions are exploring virtual banks, offering seamless transactions through virtual reality interfaces. Even healthcare is leveraging the metaverse to simulate complex surgeries and explore innovative medical treatments.

However, as with any new technology, the metaverse also brings new challenges, risks, and threats that need to be addressed by cybersecurity professionals and business leaders. The metaverse is a complex environment that’s highly interconnected, which creates new kinds of cybercrime and attack surfaces. Cybersecurity in the metaverse involves the security of the hosting platform, the property, and the users of the property.

Cybersecurity Challenges and Risks in the Metaverse

The metaverse is not immune to cyberattacks. In fact, it may be more vulnerable than the traditional web due to its novelty, complexity, and diversity. Some of the cybersecurity challenges and risks that organizations may face in the metaverse include:

Lack of regulations: The metaverse is still an emerging phenomenon that has not been fully regulated by governments or industry standards. This creates uncertainty and ambiguity for both platform owners and property owners regarding their rights and responsibilities. For example, who owns the data generated by users in the metaverse? Who is liable for any damages caused by cyberattacks or malicious actors? How can intellectual property rights be enforced in the metaverse? What are the obligatory AI ethics for the metaverse? These are some of the questions that need to be clarified and addressed by legal frameworks and policies.
Identity theft: The metaverse allows users to create and customize their respective avatars and personas that represent them in the virtual world. However, this also creates opportunities for identity theft and impersonation by cybercriminals who can use AI-generated deepfakes to create realistic and convincing fake images or videos of individuals or organizations. Deepfakes can be used for various malicious purposes, such as fraud, extortion, blackmail, defamation, or propaganda.
Data breaches: The metaverse generates massive amounts of data from user interactions, transactions, preferences, behaviours, emotions, biometrics, and more. This data is valuable for both legitimate and illegitimate purposes. For example, data can be used to improve user experience, personalize content, offer recommendations, or provide insights. However, data can also be used to target users with phishing attacks, spam messages, malware infections, or ransomware demands. Data breaches can expose sensitive information that can compromise user privacy or security.
The recent compromise of the MOVEit Transfer file management software; a computer program used by over 600 organizations worldwide including UK Ofcom, US Department of Energy, Deutsche Bank, PwC, and EY; is reported to have affected nearly 40 million people. The hydra-headed data breach incident of such magnitude perhaps underscores the possible damages that could be caused if something similar were to happen in the metaverse.
Malware infections: The metaverse relies on various devices and platforms to deliver its services and experiences. These devices and platforms may have vulnerabilities that can be exploited by hackers to inject malware into the system. Malware infections can disrupt or damage the functionality or performance of the devices or platforms or steal or encrypt data from them. Malware infections can also spread from one device or platform to another through network connections or user interactions.
Cyberattacks on critical infrastructure: The metaverse depends on critical infrastructure such as power grids, telecommunications networks, cloud servers, or IoT devices to operate smoothly and reliably. However, these infrastructure components may also be targeted by cyberattacks that aim to cause physical or digital harm or disruption.
For example, cyberattacks on power grids could cause blackouts or brownouts that affect millions of users in the metaverse. Cyberattacks on telecommunications networks could cause latency or connectivity issues that degrade user experience or prevent access to the metaverse. Cyberattacks on cloud servers could compromise data integrity or availability or cause service outages. Cyberattacks on IoT devices could hijack or manipulate their functions or data.

Cybersecurity Solutions for the Metaverse: Thriving amidst Adversity

The metaverse poses significant cybersecurity challenges and risks that require proactive and comprehensive solutions from organizations. Some of the cybersecurity solutions that organizations can implement to protect themselves and their users in the metaverse include:

Establishing cybersecurity governance: Your organization should develop and enforce a proactive cybersecurity governance model that includes clear and consistent policies and standards. These policies and standards should cover aspects such as privacy-by-design principles, privacy-by-default tenets, data ownership, data protection, data sharing, user consent, user verification, user behaviour, user feedback, user rights, user responsibilities, system status, dispute resolution, incident response, and compliance.
Ensuring regulatory compliance: To ensure and promote a more compliant predisposition amidst a shifting metaverse landscape and ever-changing regulations, your organization should adopt a proactive approach involving regular audits and swift adaptation.
Educating and empowering users: Your organization should educate and empower its users in the metaverse. You should inform users about the potential cybersecurity risks and threats that they may encounter in the metaverse and how to avoid or mitigate them. You should also provide users with the necessary tools and resources to protect themselves and their data in the metaverse, including privacy settings, security settings, reporting mechanisms, feedback mechanisms, or security awareness training.

Cybersecurity Opportunities in the Metaverse

The metaverse is not only a source of cybersecurity challenges and risks but also a source of cybersecurity opportunities for organizations. Some of the cybersecurity opportunities that organizations can leverage in the metaverse include:

Enhancing user experience: Organizations can use cybersecurity as a competitive advantage to enhance user experience in the metaverse. They can offer their users a secure, reliable, and trustworthy environment that fosters confidence, loyalty, satisfaction, and engagement. They can also use cybersecurity as a differentiator to attract new users or retain existing users who value security as a key factor in their decision-making.
Expanding business opportunities: Organizations can use cybersecurity as a catalyst to expand their business opportunities in the metaverse. They can explore new markets or segments that are emerging or growing in the metaverse. They can also create new products or services that address the specific needs or demands of users in the metaverse.
Innovating business models: Organizations can use cybersecurity as an enabler to innovate their business models in the metaverse. They can adopt new ways of delivering value to their customers or stakeholders in the metaverse. They can also leverage new sources of revenue or cost savings that are enabled by cybersecurity technologies or practices in the metaverse.

What isn’t hard to imagine for us in cybersecurity is that the metaverse is going to greatly expand the threat landscape. So, the metaverse is more than an imaginative exercise for us; it’s the future – a future we should ideally start planning for now.
— Jonathan Singer, Senior Product Marketing Manager, Checkmarx

Final thoughts

The metaverse is a promising phenomenon that offers unprecedented opportunities for organizations to create immersive and engaging experiences for their users.

However, the metaverse and Generative AI will become more pervasive, diverse, and complex, requiring more advanced and adaptive cybersecurity solutions, posing significant challenges and risks for organizations to secure their platforms, properties, and users from cyberattacks or malicious actors.

Therefore, businesses and organizations need to adopt proactive and comprehensive cybersecurity solutions that can protect themselves and their users in the metaverse while leveraging its potential benefits. They should adopt best practices and recommendations to enhance their cybersecurity posture and resilience in the metaverse, such as adopting a cyber resilience strategy, implementing a zero-trust model, using blockchain technology, leveraging artificial intelligence tools, establishing clear policies, standards, guidelines, roles, responsibilities for cybersecurity management, and collaborating with other stakeholders in the metaverse ecosystem.

If you need help developing and implementing effective cyber resilience strategies within your organization, or you’re simply interested in learning more about effective cybersecurity and risk management best practices, then please feel free to contact me today.

また会うまで – take care, until we meet again.

July 25 2023

False Assurance in Risk Management and Cybersecurity: Unmasking the Illusion

Raphael Iloh Business Continuity, Business Strategy, Cyber Security, Cybersecurity Governance, Infosec, Leadership, Risk Assessment, Risk Management, Security Architecture, Security Assurance, Security Risks, Security Strategy, Third-Party Risk Management cyber risks, cyber threats, cyberrisks, cybersecurity, cybersecurity governance, cyberthreats, false assurance, leadership, risk management, security assurance, security audit, third party risk management

In today’s interconnected digital landscape, risk management and cybersecurity are of paramount importance for organizations and individuals alike. With the constant evolution of cyber threats, it is crucial to remain vigilant and proactive in implementing robust security measures.

However, a dangerous phenomenon known as false assurance can undermine even the most well-intentioned efforts. In a previous article, I mentioned the reports of recent unconnected breaches that affected Microsoft Azure and PwC, highlighting the potentially severe impacts that come with third-party security incidents. A more recent report indicates that the number of organizations impacted by the breach incident at Microsoft Azure may have even widened in the last few days.

In this article, we’ll delve into the captivating realm of risk management and cybersecurity, uncovering the deceptive notion of false assurance; exploring its causes, implications, and strategies to mitigate its detrimental effects.

Understanding False Assurance

False assurance in risk management and cybersecurity refers to situations where organizations or individuals mistakenly believe that they are adequately protected against risks and threats, when; in reality; their security measures are ineffective or inadequate.

False assurance occurs when there is a false sense of security, leading to complacency, overconfidence, negligence, and the assumption that all necessary precautions have been taken. It can also stem from a lack of awareness, understanding, or communication of actual risks and vulnerabilities that exist in the operating environment. Unfortunately, this perception gap can expose entities (i.e., organizations and individuals) to severe consequences, including data breaches, financial loss, reputational damage, and regulatory non-compliance.

Causes of False Assurance

False assurance can arise due to several reasons including:

Inadequate risk assessment: Organizations may fail to conduct comprehensive risk assessments, leading to an incomplete understanding of potential vulnerabilities. Overlooking critical risks can create a false sense of security.
Overreliance on technology: While technological solutions play a crucial role in cybersecurity, relying solely on them without considering the human factor or other potential attack vectors can be dangerous. Organizations must adopt a holistic approach to security.
Lack of continuous monitoring: Cyber threats are constantly evolving, necessitating ongoing monitoring and adaptation of security measures. Failure to regularly assess and update security practices can result in false assurance.
Insufficient training and awareness: Human error remains a leading cause of cybersecurity breaches. If employees are not adequately trained on security best practices or are unaware of potential risks, they may engage in risky behaviour, leading to a false sense of security.
Compliance-driven approach: While compliance with regulations and standards is crucial, a compliance-focused mindset can create false assurance. Organizations must recognize that compliance does not automatically ensure security and should go beyond the minimum requirements.
Human factors: People may have cognitive biases, such as confirmation bias, optimism bias, or availability bias, which may influence their perception and judgment of risks. They may also have emotional factors, such as fear, pride, or loyalty, which affect their willingness and ability to report or address risks. Also, they may have behavioural factors, such as inertia, fatigue, or habituation, which may reduce their vigilance and responsiveness to risks.
Organizational factors: Organizations may have cultural factors, such as norms, values, or incentives, that shape their attitude and approach to risk management. They may also have structural factors, such as hierarchy, silos, or bureaucracy, that hinder their coordination and collaboration on risk management. Also, they may have procedural factors, such as policies, standards, or audits, that create a false sense of security or compliance without ensuring actual effectiveness or improvement.
Technical factors: Technologies may have inherent limitations, flaws, or vulnerabilities that expose them to risks. They may also have complex interactions or dependencies that create unforeseen risks. They may also have dynamic changes or updates that introduce new risks or invalidate existing controls.

Implications of False Assurance

The ramifications of false assurance in risk management and cybersecurity can be significant; these may include:

Increased vulnerability: False assurance blinds organizations to potential risks, leaving them exposed to sophisticated cyberattacks that can bypass inadequate security measures. Cyberattacks can cause various damages, such as data theft, encryption, deletion, or manipulation; system infection, corruption, or disruption; or network slowdown, overload, or outage.
Financial losses: Data breaches and security incidents can result in substantial financial losses due to legal liabilities, remediation costs, regulatory fines, and reputational damage.
Damage to reputation: A security breach can erode customer trust and confidence, leading to reputational damage that is difficult to recover from. Customers may choose to take their business elsewhere, impacting an organization’s long-term viability.
Legal and regulatory consequences: Organizations failing to meet their legal and regulatory obligations may face severe penalties, legal action, and loss of business licenses. Compliance failures can result from several factors, such as ignorance, misinterpretation, misalignment, or non-conformance.

These risks and threats can have severe and lasting impacts on the performance, reputation, and sustainability of any organization.

Investors see data breaches as a threat to a company’s material value and feel discouraged in investing in a business that has had its sensitive information compromised.
— Malcolm Marshall, Global Head of Cyber Security, KPMG

Mitigating False Assurance

To mitigate the risks associated with false assurance, organizations must adopt a proactive and comprehensive approach to risk management and cybersecurity. This approach may include the following:

Thorough risk assessment: Conduct comprehensive risk assessments, considering internal and external factors. This step entails identifying potential vulnerabilities, assessing potential impacts, and prioritizing security measures accordingly. Regular reviews and updates are essential to adapt to the ever-changing threat landscape.
Multi-layered security strategy: Recognize that no single solution can provide foolproof protection. Implement a multi-layered security approach that includes a combination of technological solutions, employee training, incident response plans, and regular security audits.
Continuous monitoring and adaptation: Regularly monitor systems and network traffic for suspicious activity. Stay informed about emerging threats and update security measures accordingly.
Embrace Innovation: Stagnation is the enemy of cybersecurity. By embracing innovation, organizations can stay one step ahead of malicious actors. Regularly evaluate emerging technologies, implement robust patch management processes, and foster a culture of continuous learning to promote resilience.
Employee training and awareness: Educate employees about security best practices, potential risks, and their roles and responsibilities in maintaining a secure environment. Foster a culture of cybersecurity awareness.
Independent validation: Seek external validation through independent audits, penetration testing, or cybersecurity assessments to ensure that security measures are effective and up to date.
Cybersecurity governance framework: A framework is a set of standards, guidelines, or best practices that can help organizations design, implement, and manage their respective cybersecurity program. A cybersecurity governance framework can help an organization align its cybersecurity objectives with its business goals, identify and prioritize risks, and measure and improve performance.

Key stakeholders often underestimate how complex and overwhelming it can be to manage all the ancillary people and groups who must play a role in mitigating a major breach incident, including internal and external attorneys, internal and external investigators, law enforcement, regulators, and many others.
— Bryan Sartin, Managing Director, Verizon

Closing thoughts

False assurance is a dangerous and treacherous illusion that can undermine an organization’s risk management and cybersecurity capabilities and resilience, leading to complacency and a failure to adequately protect against evolving cyber threats. It can stem from various human, organizational, or technical factors that create a gap between perception and reality of risks and vulnerabilities.

Organizations must recognize the causes and implications of false assurance and take proactive steps to mitigate its risks. By embracing a comprehensive and dynamic approach to security, organizations can strengthen their defences, protect sensitive information, and preserve their reputation in an increasingly challenging digital landscape.

Remember, true cybersecurity requires constant vigilance and adaptability.

If you need help establishing effective cybersecurity capabilities with your organization, or you’re simply interested in learning more about effective cybersecurity and risk management best practices, then please feel free to contact me today.

Au revoir; take care, until we meet again.

Bridging the Gap: Leadership Strategies for Effective Cybersecurity Governance – Part 2

Raphael Iloh Business Strategy, Cybersecurity Governance, Leadership, Risk Management, Security Architecture, Security Risks, Security Strategy, Third-Party Risk Management best practices, business agility, business continuity, compliance, cyber risks, cyber threats, cyberrisks, cybersecurity governance, cyberthreats, grc, information security, innovation, kpi, kri, leadership, okr, organizational change, organizational culture, policies, risk management, standards, technology

Within the last week or so, we’ve seen reports of a couple of serious breaches that put the reputation of the target organizations in jeopardy but, more importantly, these breaches also constituted significant third-party risks to businesses and organizations that rely on the affected organizations. The first reported breach hit Microsoft Azure and impacted some users of its email services. The second reported breach targeted PwC and impacted some of its clients.

Sadly, cyber-attacks and cyber-incidents are nearly almost inevitable, it’s the nature of the beast.

However, whilst likelihood is almost nearly certain, severity and impact can be reduced, significantly. The adverse impacts of any such events on the operations of your organization can be mitigated and contained. And as a cybersecurity leader, one of the effective tools that can help you build resilience in the defence of your organization is effective cybersecurity governance.

To establish and maintain effective cybersecurity governance, leaders must develop a comprehensive cybersecurity strategy. This entails identifying critical assets and vulnerabilities, implementing risk management frameworks, and ensuring robust governance structures to guide their decision-making, planning, implementation, and evaluation of cybersecurity initiatives.

In the previous article, we looked at the crucial role of leadership in establishing and maintaining robust cybersecurity governance. We explored the qualities and skills required for cybersecurity leaders to navigate the complexities of the evolving threat landscape, address the challenges posed by these emerging threats, satisfy regulatory compliance, foster a culture of security awareness, and drive organizational change.

This article is the second and final part in the series. In this article, we’ll delve into some practical hands-on strategies that can help cybersecurity leaders establish and maintain effective cybersecurity governance within their organizations. Some of these strategies include:

Define your vision and strategy for cybersecurity

As a cybersecurity leader, you should define your vision and strategy for cybersecurity that aligns with your organization’s mission, vision, and values. Your vision should describe what you want to achieve in terms of cybersecurity outcomes, such as security posture, resilience, compliance, reputation, etc.

Your strategy should outline how you plan to achieve your vision by setting Specific, Measurable, Achievable, Relevant, and Time-bound (SMART) goals and objectives. You should also identify the key building blocks for your strategy i.e., drivers, enablers, and barriers.

Here are some examples of outlined key building blocks:

Vision: To be recognized as a leader in cybersecurity excellence by our customers, partners, regulators, and peers.
Strategy: To implement a comprehensive cybersecurity program that covers all aspects of our business operations, from strategy to execution.
Goal #1: To achieve ISO/IEC 27001 certification by Q4 2024.
Goal #2: To reduce the number of security incidents by 50% by Q2 2024.
Goal #3: To increase the level of security awareness among our employees by 80% by Q1 2025.
Driver: To protect our brand reputation; to comply with regulatory requirements.
Enabler #1: To allocate sufficient resources and budget for cybersecurity.
Enabler #2: To develop policies and standards for cybersecurity.
Enabler #3: To establish clear roles and responsibilities for cybersecurity.
Enabler #4: To monitor performance and compliance for cybersecurity.
Enabler #5: To engage stakeholders and partners for cybersecurity.

This bit is rather particularly important; you should align your vision and strategy with the overall vision and strategy of your organization, as well as ensure that they are consistent and coherent.

Once you have defined your vision and strategy for cybersecurity, you should communicate it to your team, your peers, and other relevant stakeholders. Also, you should review and update your vision and strategy regularly, based on the feedback, results, and changes in the environment.

Build your team and empower them

As a cybersecurity leader, you’d build a strong and diverse team that can support you in implementing your vision and strategy for cybersecurity. You should recruit, train, develop, and retain the best talent for cybersecurity, based on their skills, experience, knowledge, attitude, and potential. You should also leverage the existing capabilities and resources within your organization, such as IT, legal, compliance, audit, risk, etc.

You should also empower your team by delegating authority and responsibility for cybersecurity tasks and activities. You should provide them with clear expectations, guidance, support, feedback, and recognition. You should also encourage them to collaborate with each other and with other teams and stakeholders. You should also foster a culture of learning and improvement within your team by promoting continuous education, training, certification, mentoring, coaching, etc.

Develop policies, standards, and procedures for cybersecurity

You should develop policies, standards, and procedures for cybersecurity that define the rules, requirements, and best practices for securing your organization’s systems and information. You should base your policies and standards on recognized frameworks, such as ISO/IEC 27001, NIST Cybersecurity Framework (CSF), NIST Risk Management Framework (RMF), or COBIT.

You should ensure that the policies, standards, and procedures you develop are aligned with the values, principles, and objectives of your organization. Also, you should ensure that the policies and standards are documented, communicated, and enforced across the organization. You should also monitor compliance with your policies and standards, as well as take corrective actions when needed.

Implement controls and measures for cybersecurity

As a cybersecurity leader, you should implement controls and measures for cybersecurity that protect your organization’s systems and information from cyber threats and attacks. You should base your controls and measures on recognized models, such as CIA (Confidentiality, Integrity, & Availability), AAA (Authentication, Authorization, & Accountability), or PDCA (Plan, Do, Check, Act).

You should ensure that the controls and measures you implement align with the risk appetite, business needs, and stakeholder expectations within your organization.

Also, you should ensure that your controls and measures are effective, efficient, and economical. You should also measure (and report on) the performance of your controls and measures using relevant metrics, such as Key Performance Indicators (KPIs), Key Risk Indicators (KRIs), or Key Control Indicators (KCIs). You should also improve your controls and measures regularly, based on the feedback, results, and changes in the environment.

Companies that are leveraging technologies the best, leveraging the best practices in order to mitigate their risk, they should see that reflected in the terms and conditions that they are offered by the market…
— Noel Pearman, XL Catlin

Review risks and opportunities for cybersecurity

You should review risks and opportunities for cybersecurity to ensure that your organization is prepared for the current and future cyber threat landscape. You should use various tools and techniques to identify, analyse, evaluate, and treat risks and opportunities related to cybersecurity. Some of these tools and techniques include:

Risk identification: To recognize sources, events, or causes of potential or actual harm or loss related to cybersecurity.
Risk analysis: To estimate the likelihood and impact of potential or actual harm or loss related to cybersecurity.
Risk evaluation: To compare the level of risk with the organization’s risk appetite or tolerance related to cybersecurity.
Risk treatment: To select and implement options to avoid, reduce, transfer, or accept risk related to cybersecurity.
Opportunity identification: To recognize sources, events, or causes of potential or actual benefit or gain related to cybersecurity.
Opportunity analysis: To estimate the likelihood and impact of potential or actual benefit or gain related to cybersecurity.
Opportunity evaluation: To compare the level of opportunity with the organization’s opportunity appetite or criteria related to cybersecurity.
Opportunity treatment: To select and implement options to exploit, enhance, share, or ignore opportunities related to cybersecurity.

As always, you should ensure that your review activities are proactive, comprehensive, systematic, and consistent. Also, you should communicate your review results to relevant stakeholders using appropriate formats and channels. You should also act on your review results by taking preventive or corrective actions when needed.

Engage stakeholders and partners for cybersecurity

You should engage stakeholders and partners for cybersecurity to ensure that your organization has the support and collaboration it needs to achieve its security goals and objectives. You should identify who your stakeholders and partners are, what their interests and expectations are, and how you can communicate and interact with them effectively. Some of your stakeholders and partners may include:

Internal stakeholders: Such as senior executives, board members, managers, employees, etc., who have a direct or indirect interest in the organization’s security performance or compliance.
External stakeholders: Such as customers, suppliers, regulators, auditors, investors, media, etc., who have a direct or indirect influence on the organization’s security performance or compliance.
Partners: Such as peers, competitors, industry associations, professional bodies, academic institutions, research organizations, etc., who have a common interest or goal in enhancing security performance or compliance.

You’d expect to use various tools and techniques to engage stakeholders and partners including Stakeholder analysis, Stakeholder engagement plan, communication plan, etc. You’d communicate your engagement results to relevant stakeholders and partners using appropriate formats and channels.

Other elements that you would cover in your overarching cybersecurity governance include:

Monitor performance and compliance for cybersecurity.
Promote awareness and education for cybersecurity.
Establish vendor and third-party risk management.
Establish and monitor business continuity and disaster recovery plans.
Establish asset inventory and management.
Drive innovation and improvement for cybersecurity.
Integrate with the enterprise architecture.

Fix the basics, protect first what matters for your business and be ready to react properly to pertinent threats. Think data, but also business services integrity, awareness, customer experience, compliance, and reputation.
— Stéphane Nappo

Final thoughts

Cybersecurity governance is a strategic imperative that affects every aspect of an organization’s operations, performance, reputation, and resilience. It requires strong leadership from the top down and across all levels of the organization. Effective cybersecurity leaders possess a combination of qualities and skills that enable them to lead by example, inspire others, and deliver results. They also employ various strategies that can help them establish and maintain effective cybersecurity governance within their organizations. By following these strategies, cybersecurity leaders can bridge the gap between their vision and reality for cybersecurity and create a robust security culture within their organizations.

I hope that this set of articles has empowered you, as a cybersecurity leader, to champion cybersecurity initiatives and create a robust security culture within your organization. I also hope that these articles have inspired further research or practice on cybersecurity governance.

Au revoir; take care, until we meet again.

Bridging the Gap: Leadership Strategies for Effective Cybersecurity Governance

Raphael Iloh Business Continuity, Business Strategy, Cyber Security, Infosec, Leadership, Risk Assessment, Risk Management, Security Architecture, Security Risks, Security Strategy best practices, business agility, business continuity, compliance, cyber risks, cyber threats, cyberrisks, cybersecurity governance, cyberthreats, grc, information security, innovation, kpi, leadership, organizational change, organizational culture, policies, risk management, standards, technology

Cybersecurity is no longer a technical issue that can be delegated to IT departments. It is a strategic imperative that affects every aspect of an organization’s operations, performance, reputation, and resilience. In the digital age, cybersecurity threats are constantly evolving and becoming more sophisticated, posing significant challenges and risks to organizations of all sizes and in pretty much all sectors.

As the world around us is evolving and becoming more digital, the collective understanding of what it means to be safe, secure, and resilient is also evolving. According to the Harvard Business Review (HBR), the impact of cybercrime is predicted to reach US$10 trillion this year. In the same report, HBR indicated that human error constitutes the biggest cyber-threat as it accounts for over 80% of cyber-incidents.

How can organizations effectively protect themselves and their stakeholders from cyber-threats, cyber-risks, and cyber-incidents, while also enabling innovation and growth?

I’d argue that, in nearly all cases, the answer most probably lies in effective cybersecurity governance.

In a couple of previous posts; part 1 and part 2 of a series on cybersecurity and the supply chain; I discussed some ways to safeguard the digital fortress including the use of effective cybersecurity governance. Cybersecurity governance is how organizations control and direct their approach to cybersecurity, including defining their risk appetite, building accountability frameworks, and establishing who is responsible for making decisions.

Effective cybersecurity governance will help ensure that cybersecurity activities support the organization’s overarching strategic mission/goals, align with its values, and culture, as well as comply with its legal and regulatory obligations. Effective cybersecurity governance will also enable the organization to respond quickly and effectively to emerging threats and incidents, as well as to communicate clearly and confidently with its stakeholders.

However, achieving effective cybersecurity governance is not easy. It requires strong leadership from the top, as well as collaboration and engagement from all levels of the organization. It also requires a clear vision, a robust strategy, and a flexible framework that can adapt to changing conditions and needs.

In this article, we’ll explore the essential role of leadership in establishing and maintaining effective cybersecurity governance, as well as provide practical insights and strategies for cybersecurity leaders to bridge the gap between security and business objectives.

The Role of Leadership in Cybersecurity Governance

Leadership is the key factor that determines the success or failure of cybersecurity governance. Leadership could be described as the ability of an entity (i.e., an individual, a group, a team, or an organization) to influence or guide other entities to achieve common or shared objectives.

Without any doubt, leadership involves setting direction, communicating vision, motivating action, empowering people, building trust, resolving conflicts, and ensuring accountability. Within any organization, ensuring that policies, standards, principles, and procedures are properly developed and maintained requires a well-defined governance model, such as the one outlined in ISO/IEC 27014-2020.

In the context of cybersecurity governance, leadership plays a vital role in:

Defining the organization’s vision and strategy for cybersecurity
Establishing clear roles and responsibilities for cybersecurity
Informing the organization’s decision concerning investments in cybersecurity.
Allocating adequate resources and budget for cybersecurity
Developing policies and standards for cybersecurity
Implementing controls and measures for cybersecurity
Monitoring performance and compliance for cybersecurity
Reviewing risks and opportunities for cybersecurity
Engaging stakeholders and partners for cybersecurity
Promoting awareness and education for cybersecurity
Driving innovation and improvement for cybersecurity

Cybersecurity leaders are those who have the authority, responsibility, and accountability for overseeing and managing cybersecurity within their organizations. They may have different titles, such as Chief Information Officer (CIO), Chief Technology Officer (CTO), Chief Information Security Officer (CISO), Chief Security Officer (CSO), Principal Cybersecurity Consultant, or team leader but they share a common goal: to ensure that their organizations are secure, resilient, and compliant.

These leaders need to have a range of qualities and skills to fulfil their roles effectively. They need to have a deep understanding of the technical aspects of cybersecurity, as well as the business context and environment in which they operate. Also, they need to have a strategic mindset, as well as an operational focus. Furthermore, they need to have strong communication skills, as well as analytical abilities. They need also to have a collaborative attitude, as well as a decisive approach. They need to have a visionary outlook, as well as a pragmatic perspective.

Until you have experienced something like this, you don’t realise just what can happen, just how serious it can be… I had no intuitive idea on how to move forward.
— Soren Skou, CEO, Maersk

Understanding the Complex Challenges

The ever-changing cybersecurity landscape presents organizations with a myriad of challenges. From sophisticated cyber threats to legal and regulatory compliance, leaders must be well-informed and adaptable. As a cybersecurity leader, you’d expect to face complex challenges, such as:

Align security goals with business objectives: You need to ensure that your security strategy supports your organization’s vision, mission, values, and goals. You need to balance the trade-offs between security and performance, between risk mitigation and innovation, and between compliance and competitiveness. You need to demonstrate the value of security investments and initiatives to senior management and other stakeholders, as well as justify the allocation of resources and priorities.
Manage risks and compliance: You need to identify, assess, prioritise, treat, monitor, and report on the cyber risks that your organization faces. You need to establish a risk appetite framework that defines the level of risk that your organization is willing to accept or tolerate in pursuit of its objectives. You need to implement appropriate controls and measures to reduce or transfer the risks that exceed the risk appetite. Also, you need to ensure that your organization complies with relevant laws, regulations, standards, policies, and best practices.
Respond to emerging threats and incidents: A proactive incident response culture is another hallmark of effective cybersecurity governance. As a cybersecurity leader, you need to be aware of the current threat landscape and the potential impact of cyberattacks on your organization. You need to develop and maintain an incident response plan (or playbook, if you will) that defines roles, responsibilities, processes, procedures, tools, and resources for detecting, containing, analysing, resolving, recovering from, learning from, and communicating about cyber incidents. Also, you need to test and exercise your team’s incident response capabilities regularly.
Foster a culture of security awareness: You need to create a culture where security is everyone’s responsibility within your organization. You need to educate and train staff on security policies, procedures, practices, and behaviours. You need to raise awareness of cyber threats and risks, and how to prevent or report them. You need to reward positive security actions and outcomes, as well as address negative ones. Also, you need to lead by example and demonstrate your commitment to security.
Foster a culture of security innovation: As a cybersecurity leader, you’d champion a culture of innovation within your teams and organization by encouraging curiosity, research, creative thinking, design thinking, risk-taking, and a mindset of learning from mistakes.

As cybersecurity leaders, we have to create our message of influence because security is a culture, and you need the business to take place and be part of that security culture.
— Britney Hommertzheim

Trust in the digital business age is every bit as important as actual service delivery. Few things impact a company’s brand more than a badly handled data breach or prolonged service outage.
— Hugh Callaghan, Executive Director, Cyber Advisory Services, EY

Conclusion

Cybersecurity leadership is essential for effective cybersecurity governance. In this article, we’ve explored the essential role of leadership in establishing and maintaining effective cybersecurity governance within organizations. We’ve examined the qualities and skills required for cybersecurity leaders to navigate complex challenges, foster a culture of security awareness, and drive organizational change for cybersecurity governance.

In the follow-up article, we’ll delve into some practical hands-on insights and strategies for cybersecurity leaders to help them bridge the gap between security and business objectives, as well as create a robust security culture within their respective organizations.

Au revoir; take care, until we meet again.

July 16 2023

Safeguarding the Digital Fortress: Navigating Cybersecurity and Supply Chain Challenges – Part 2

Raphael Iloh Business Strategy, Cyber Security, Leadership, Risk Assessment, Risk Management, Security Architecture, Security Risks, Security Strategy, Supply Chain Risk Management, Third-Party Risk Management business agility, business continuity, cscrm, cyberattacks, cybersecurity, cyberthreats, disaster recovery, governance, kpi, leadership, ncsc, nist, okr, risk management, supply chain, third party risk management

This is the second part of a 2-part series wherein we explore cybersecurity and supply chain challenges. In the first post, we explored the challenges, risks, and threats that cybersecurity and the supply chain pose to organizations and how these could be effectively mitigated against. We also looked at how cybersecurity supply chain risks touch nearly all facets of business operations including sourcing, vendor management, supply chain continuity and quality, transportation security and many other functions across the enterprise.

The digital landscape is fraught with diverse cybersecurity threats, ranging from malware and phishing attacks to the ever-looming threat of ransomware. Such threats not only compromise data integrity but also disrupt operations and tarnish the reputation of businesses. In this second and final part of the series, we’ll delve even further into a few other factors that play into the complex yet critical fabric of the global interconnectedness of businesses and organizations. Let’s get started, shall we?

A holistic approach to C-SCRM

Cybersecurity and the supply chain are interdependent and mutually influential. C-SCRM is a vital process that helps organizations to ensure the security and integrity of their products and services and to mitigate the risks and threats that may affect their supply chain.

To be effective, C-SCRM must be seen and conducted as an enterprise-wide activity that involves all tiers of your organization i.e., people, business processes, and technology. C-SCRM requires a holistic and proactive approach that involves collaboration among all parties in the supply chain and incorporates other aspects of cybersecurity such as generative AI, data protection, leadership, cyber resilience, privacy, third-party risks, and cybersecurity governance.

Generative AI for C-SCRM

The emergence of Generative AI, a subset of Artificial Intelligence (AI), has brought new possibilities for enhancing cybersecurity. Generative AI can be a powerful tool for C-SCRM in several ways, such as:

Enhancing the security and quality of products and services by using generative AI to test, verify, or validate their functionality, performance, or compliance.
Improving the efficiency and agility of supply chain processes by using generative AI to automate, optimize, or streamline tasks such as design, development, distribution, deployment, maintenance, etc.
Increasing the innovation and differentiation of products and services by using generative AI to generate new features, functionalities, or designs that meet customer needs or expectations.
Enabling the personalization and customization of products and services by using generative AI to tailor them to specific preferences, contexts, or scenarios of customers or users.

However, there are some challenges and risks of integrating Generative AI into C-SCRM, such as:

Introducing new vulnerabilities or threats to products and services by using generative AI to create malicious or harmful content or data that can compromise their security or integrity.
Reducing the transparency or accountability of products and services by using generative AI to generate content or data that is difficult to explain, verify, or trace.
Increasing the complexity or uncertainty of products and services by using generative AI to generate content or data that is dynamic, unpredictable, or probabilistic.
Affecting the ethics or legality of products and services by using generative AI to generate content or data that is inappropriate, offensive, deceptive, or infringing.

Therefore, it is important to use generative AI responsibly and ethically for C-SCRM and ensure that it complies with the relevant standards, regulations, and best practices.

A reinforced and sturdy C-SCRM

C-SCRM is not a standalone activity but rather an integral part of the overall cybersecurity strategy and culture of an organization. Therefore, it’s essential to incorporate other key aspects of cybersecurity such as data protection, leadership, cyber resilience, privacy, third-party risks, and cybersecurity governance into C-SCRM. Some of the ways to do this include:

Data protection: Ensure that the data that is collected, processed, stored, transmitted, or shared in the supply chain is protected from unauthorized access, use, disclosure, modification, or destruction. Implement data protection measures such as encryption, authentication, authorization, backup, recovery, etc. Comply with data protection laws and regulations such as GDPR, CCPA, etc.
Leadership: Establish a clear vision and direction for C-SCRM that is communicated and supported by the top management and stakeholders. Empower and enable the C-SCRM team with the necessary resources, authority, and accountability. Foster a culture of trust, collaboration, and continuous improvement among all parties in the supply chain.
Cyber resilience: Build the ability to anticipate, prepare for, respond to, and recover from cyberattacks in the supply chain. Develop a cyber resilience strategy that covers prevention, detection, response, recovery, and learning. Implement cyber resilience measures such as redundancy, diversity, modularity, adaptability, etc.
Privacy: Privacy is a complex and evolving domain that requires balance and trade-offs. It’s subject to various interests and values that may conflict or compete with each other. Respect the rights and preferences of customers and users regarding their personal information in the supply chain. Implement privacy measures such as consent, notice, choice, access, rectification, erasure, etc. Comply with privacy laws and regulations such as GDPR, CCPA, etc.
Your organization can implement privacy standards and frameworks (e.g., ISO/IEC 29100, NIST SP 800-53A, or CIS Privacy Controls) that provide guidance on how to embed privacy principles and practices into its data processing activities.
Third-party risks: Third-party risk management is subject to various sources and types of risks that may change or evolve over time. Some examples of such sources and types of risks include performance risks, financial risks, operational risks, strategic risks, compliance risks, or reputational risks. Assess and manage the risks associated with the external parties that provide products or services in the supply chain. Implement third-party risk management measures such as due diligence, risk assessment, contract management, monitoring, auditing, etc.
Your organization can comply with third-party risk management standards and frameworks such as ISO 27036 (parts 1 through 4), NIST SP 800-161, etc.
Cybersecurity governance: Cybersecurity governance is a challenging and demanding domain that requires leadership, culture, and competence. Cybersecurity governance is subject to various stakeholders and expectations that may vary by sector, industry, or region. Some examples of such stakeholders and viewpoints include board members, senior managers, employees, customers, suppliers, regulators, and auditors. Establish and maintain the policies, processes, structures, roles, and responsibilities for C-SCRM. Implement cybersecurity governance measures such as planning, organizing, directing, controlling, reporting, etc.
Your organization can implement cybersecurity governance standards and frameworks such as ISO 27001, ISO 38500, NIST SP 800-37, NIST CSF, COBIT, etc. Your organization can also invest in cybersecurity governance tools to help enhance its cybersecurity governance capabilities and performance. Such tools and training include cybersecurity governance dashboard, cybersecurity governance scorecard, cybersecurity governance maturity model, cybersecurity governance workshop, etc.

NIST has outlined some key practices for effective C-SCRM alignment including:

Integrate C-SCRM across the organization.
Establish a formal C-SCRM program.
Know and manage critical suppliers.
Understand the organization’s supply chain.
Closely collaborate with key suppliers.
Include key suppliers in resilience and improvement activities.
Assess and monitor throughout the supplier relationship.
Plan for the full lifecycle.

Experts on cybersecurity and supply chain management like to draw attention to the fact that operating systems are only as strong as their “weakest link“. The “weakest link” argument is evoked with good reason when discussing risk management.
— Xeneta

Conclusion

Okay, we’ve discussed the challenges and opportunities of cybersecurity and supply chain management. We’ve also discussed how Generative AI can be used to create and protect data in various domains. Finally, I’ve provided some best practices and recommendations for improving cybersecurity and supply chain management, drawing on relevant guidance and regulations such as the NCSC Supply Chain Security Guidance, the NIST CSCRM, and the EU Supply Chain Due Diligence Directive.

If you are interested in learning more about C-SCRM or need help with implementing it in your organization, please contact me today. I can help you to design, develop, and deploy a C-SCRM strategy that suits your business objectives, risk appetite, regulatory obligations, and cybersecurity posture. I can also help you to leverage generative AI for C-SCRM responsibly and ethically.

Hasta que nos encontremos de nuevo; take care, see you around soon.

July 12 2023

Safeguarding the Digital Fortress: Navigating Cybersecurity and Supply Chain Challenges – Part 1

Raphael Iloh Business Continuity, Business Strategy, Cyber Security, Leadership, Risk Assessment, Risk Management, Security Architecture, Security Risks, Security Strategy, Supply Chain Risk Management, Third-Party Risk Management business agility, business continuity, cscrm, cyberattacks, cybersecurity, cyberthreats, leadership, ncsc, nist, risk management, supply chain, third party risk management

In a previous post, I mentioned that supply chain attacks would be one of the possible cybersecurity trends to look out for in 2023. Given the ever-mounting of threats of cyberattacks to supply chains, Gartner reported that 44% of organizations indicated that they would substantially increase year-over-year spend on supply chain cybersecurity in 2023.

In the last week, there’ve been news reports of a ransomware attack on the Port of Nagoya in Tobishima, Japan’s largest port by total cargo throughput. Reports indicate that the attack had successfully prevented the port from receiving shipping containers for two days. The port is a significant hub for Toyota Motor Corporation, handling some of the company’s exports and imports.

Cybersecurity is not just about protecting your systems and data from cyberattacks. It is also about ensuring the security and integrity of the products and services you rely on from your suppliers, vendors, and partners. This is what cybersecurity supply chain risk management (C-SCRM) is all about.

This post is the first part of a 2-part series wherein we’ll explore the challenges, risks, and threats that cybersecurity and supply chain pose to organizations and how these could be effectively mitigated against. We’ll also discuss how data protection, cyber resilience, third-party risks, cybersecurity governance, and a few other factors play into this complex and critical relationship.

Finally, we’ll provide some best practices and recommendations for improving cybersecurity and supply chain management in this ever-evolving digital era, drawing on relevant guidance and regulations such as the NCSC Supply Chain Security Guidance, the NIST CSCRM Guidance, and the EU Supply Chain Due Diligence Directive.

What’s Cybersecurity Supply Chain Risk Management?

According to NIST, C-SCRM could be described as “the process of managing the cybersecurity risks that may affect the supply chain and its products and services. It involves identifying, assessing, monitoring, and responding to these risks (whether intentional or inadvertent) at all levels of an organization and its external partners. C-SCRM aims to ensure the integrity, security, quality, and resilience of the supply chain and its cybersecurity-related elements.”

C-SCRM covers the entire lifecycle of a system (including design, development, distribution, deployment, acquisition, maintenance, and destruction) and the extended circle of vendors that may use services or products from other vendors. It also covers the physical and software security of the purchased devices and programs.

Some of the factors that make the supply chain vulnerable to cyberattacks include:

The use of multiple components from various sources may have different levels of security or quality assurance.
The reliance on third-party service providers for cloud services, web applications, online stores, management software, etc.
The lack of visibility or control over the security practices of suppliers or subcontractors.
The exposure to geopolitical or regulatory risks that may affect the availability or integrity of products or services.
The possibility of insertion of counterfeits, unauthorized production, tampering, theft, insertion of malicious software or hardware, or poor manufacturing or development practices in the supply chain.

These factors can result in risks such as:

Compromise of confidential or sensitive data or intellectual property.
Loss of functionality or availability of critical systems or services.
Damage to your organization’s reputation or the trust of customers or stakeholders.
Legal liability or regulatory non-compliance.
Financial losses or operational disruptions.

How to Mitigate C-SCRM Risks?

Mitigating C-SCRM risks requires a holistic and proactive approach that involves collaboration among all parties in the supply chain. Some effective mitigating measures against cybersecurity supply chain risks include:

Establishing a C-SCRM strategy that aligns with the organization’s business objectives, risk appetite, and cybersecurity posture.
Developing a C-SCRM policy that defines roles and responsibilities, processes and procedures, standards and guidelines, metrics and reporting for managing C-SCRM risks.
Conducting a C-SCRM assessment that identifies and prioritizes the critical assets, suppliers, processes, and dependencies in the supply chain and evaluates their cybersecurity risks.
Implementing C-SCRM controls that address the identified risks through preventive, detective, corrective, or compensating measures. These may include contractual clauses, security requirements, audits, testing, monitoring, incident response, contingency planning, etc.
Monitoring C-SCRM performance that tracks and measures the effectiveness of C-SCRM controls and provides feedback for improvement.
Reviewing C-SCRM practices that periodically evaluate the relevance, adequacy, and efficiency of C-SCRM strategy, policy, assessment, controls, and performance and update them as needed.

While organizations say they are aware of the risks, most admit that they aren’t making supply chain security a priority.
— synopsys.com

Conclusion

As we conclude the first part of this exploration of cybersecurity and supply chain challenges, it’s clear that the digital fortress demands our utmost attention. Cybersecurity in the supply chain isn’t an IT problem only. Cybersecurity supply chain risks touch pretty much all facets of business operations including sourcing, vendor management, supply chain continuity and quality, transportation security and many other functions across the enterprise.

In the second part of the series, we’ll explore a few other factors that play into this complex yet critical relationship, including data protection, cyber resilience, third-party risks, cybersecurity governance, and leadership.

Hasta que nos encontremos de nuevo; take care, see you around soon.

July 3 2023

Unleashing the Power of Artificial Intelligence in Healthcare: Revolutionising Patient Care – Part 2

Raphael Iloh Artificial Intelligence, Business Strategy, Cyber Security, Healthcare, Lifestyle, Risk Management, Security Strategy, Third-Party Risk Management advancedmedicine, ai, aihealthcare, artificialintelligence, changeculture, compliance, cybersecurity, digitalhealth, generativeai, healthcare, innovation, leadership, machinelearning, patientcare, privacy, strategy, technology, unbiasedmedicine

This is the second part of a 2-part series where we delve into the realm of Artificial Intelligence (AI) in healthcare. In the first post, we discussed how AI is transforming healthcare and medicine, by providing new ways to diagnose, treat, or prevent diseases, as well as improving the delivery and quality of health services. We also discussed the applications and benefits of AI in the delivery of healthcare services, such as enhancing efficiency, accuracy, and personalisation.

However, whilst the promises of AI in healthcare are remarkable, AI for health also poses significant challenges and risks for health systems, such as ethical, social, and technical issues. So, in this second and final part of the series, join me as we discuss some of the challenges, risks, and issues that often accompany the implementation of AI, and then proffer possible solutions to ensure responsible AI adoption.

Challenges and Ethical Considerations

Ethical dilemmas: AI can raise ethical questions or conflicts that may not have clear or universal answers, such as who is responsible or accountable for the outcomes or consequences of AI systems, how to ensure fairness or equity in the access or distribution of AI benefits, or how to balance the rights or interests of different parties involved in AI systems, such as patients, providers, developers, or regulators.
Data privacy and security concerns: As healthcare systems rely heavily on sensitive patient data, safeguarding privacy and ensuring robust security measures become paramount. Proper data governance, encryption, and stringent access controls are crucial to protect patient information from breaches or misuse.
Bias and fairness in AI algorithms: AI algorithms are only as unbiased as the data they are trained on. It is essential to ensure diverse and inclusive data sets to avoid perpetuating biases. Ongoing monitoring and auditing of AI systems can help detect and rectify any unintended biases in decision-making processes.
Social implications: AI can have social impacts that may affect the values, norms, or behaviours of individuals or groups in society, such as how to preserve human dignity, autonomy, or agency in the face of AI systems, how to maintain human relationships, trust, or empathy in the context of AI systems, or how to address potential social disruptions, divisions, or inequalities that may result from AI systems.
Transparency and interpretability of AI systems:The “black box” nature of AI systems can raise concerns regarding transparency and interpretability. Healthcare professionals and regulators must work together to ensure that AI algorithms are transparent, providing insights into how decisions are made, and fostering trust among stakeholders.
Technical limitations: AI can have technical challenges that may limit its performance, reliability, or safety in real-world settings, such as how to ensure the quality, validity, or security of the data used to train or test AI systems, how to deal with uncertainty, complexity, or ambiguity in the data or environment that may affect AI systems, or how to handle errors, failures, or attacks that may compromise AI systems.
Regulatory gaps: AI can have regulatory challenges that may hinder its development, adoption, or evaluation in health systems, such as how to define, measure, or monitor the standards, criteria, or indicators for assessing the effectiveness, efficiency, or impact of AI systems, how to establish, enforce, or update the rules, guidelines, or frameworks for governing the design, use, or oversight of AI systems or how to foster collaboration, cooperation, or coordination among different stakeholders sectors or jurisdictions involved in AI systems.

Overcoming Challenges and Ensuring Responsible AI Adoption

To ensure responsible AI adoption in healthcare, some measures to overcome and mitigate these challenges and risks may include:

Develop ethical guidelines: Ethical guidelines can help provide a common vision principles or values for guiding the development use or evaluation of AI systems in healthcare. Ethical guidelines can also help address or resolve ethical dilemmas or conflicts that may arise from AI systems in healthcare. For example, the World Health Organization (WHO) issued a report on Ethics and governance of artificial intelligence for health, which provides six guiding principles for AI in health, namely:
1. Protecting human autonomy.
2. Promoting human well-being and safety and the public interest.
3. Ensuring transparency, explainability, and intelligibility.
4. Fostering responsibility and accountability.
5. Ensuring inclusiveness and equity.
6. Promoting AI that is responsive and sustainable.
Establish governance frameworks: Governance frameworks can help provide a clear and consistent structure, process, or mechanism for regulating, monitoring, or evaluating AI systems in healthcare. Governance frameworks can also help ensure the compliance, quality, or safety of AI systems in healthcare. For example, the UK National Health Service (NHS) has developed an AI in Health and Care Award programme, which provides a pathway for accelerating the testing and adoption of AI systems in healthcare, as well as a set of standards and requirements for assessing the feasibility, clinical safety, efficacy, and cost-effectiveness of AI systems in healthcare.
Establish robust data governance and protection measures: Healthcare organizations must establish robust data governance frameworks, ensuring compliance with privacy regulations and implementing stringent security protocols to protect patient data.
Ensure diverse and inclusive data sets for AI training: By actively seeking diverse and representative data sets, we can mitigate biases and ensure that AI algorithms deliver fair and equitable outcomes for all patients, irrespective of their background or demographics.
Establish regulatory frameworks and guidelines for AI deployment: Regulators play a crucial role in establishing guidelines and standards for AI deployment in healthcare. By working hand in hand with healthcare professionals and AI experts, regulators can ensure responsible AI adoption, promoting patient safety, and ethical practices.
Ensure human oversight: Human oversight can help provide a check and balance for AI systems in healthcare, by ensuring that human values, judgments, or inputs are incorporated or respected in AI systems in healthcare. Human oversight can also help prevent or correct errors, failures, or harms that may result from AI systems in healthcare. For example, the European Commission has proposed a risk-based approach for regulating AI systems in various sectors, including healthcare, which requires high-risk AI systems to have adequate human oversight measures, such as human-in-the-loop (where humans can intervene or override AI decisions), human-on-the-loop (where humans can monitor or supervise AI decisions), or human-in-command (where humans can set or limit AI goals or parameters).
Foster collaboration: Collaboration can help facilitate the sharing of knowledge, resources, or best practices among different stakeholders, sectors, or jurisdictions involved in AI systems in healthcare. Collaboration can also help promote innovation, diversity, or inclusion in AI systems in healthcare. For example, the Partnership on AI is a multi-stakeholder initiative that brings together academics, researchers, civil society organizations, companies, and governments to explore and address the opportunities and challenges of AI in various domains, including healthcare. The Partnership on AI aims to advance the understanding and application of AI in ways that are ethical, fair, transparent, accountable, and beneficial to humanity.
Promote education: Education can help raise awareness and understanding of AI among various audiences, such as patients, providers, researchers, policymakers, or the public. Education can also help develop the skills Competencies or capacities needed to design use or evaluate AI systems in healthcare. For example, the Stanford Center for Health Education has launched an online course on Artificial Intelligence in Healthcare which introduces the concept, technologies, and applications of AI in healthcare, as well as the ethical social and regulatory issues related to AI in healthcare.

The Future of AI in Healthcare

As we gaze into the future, the potential of AI in healthcare seems boundless; I dare say that we’re yet to scratch the surface of the immense potential of AI in healthcare. Emerging trends and technologies such as natural language processing, robotic surgery, and AI-driven drug discovery hold promise for revolutionizing healthcare practices. However, we must remain mindful of ethical and societal considerations, actively shaping the future of AI in healthcare through collaboration, innovation, and responsible implementation.

Eventually, doctors will adopt AI and algorithms as their work partners. This levelling of the medical knowledge landscape will ultimately lead to a new premium: to find and train doctors who have the highest level of emotional intelligence.
— Eric Topol, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

Conclusion

AI is transforming healthcare and medicine in unprecedented ways, by providing new tools methods or solutions for improving health outcomes quality and access to care. AI has many benefits for various stakeholders in health systems, such as patients, providers, researchers, policymakers, and society at large.

However, AI also poses significant challenges and risks for health systems. Therefore, it is essential to adopt a balanced and responsible approach to developing, using, and evaluating AI systems in healthcare, by following ethical guidelines, establishing governance frameworks, ensuring more comprehensive and inclusive data sets, ensuring human oversight, fostering collaboration, and promoting education.

By doing so, we can harness the potential of AI for health to revolutionize healthcare and medicine in the future, while minimizing its pitfalls and maximizing its benefits for humanity.

Au revoir; take care, until we meet again.

If you are interested in learning more about AI in healthcare, you can check out these resources:

Artificial Intelligence: Healthcare’s New Nervous System: This report by Accenture provides an overview of the current state and future trends of AI in healthcare, as well as some recommendations for health organizations to leverage AI for growth and value.
Artificial Intelligence for Health: This website by the International Telecommunication Union (ITU) provides information on the global focus group on artificial intelligence for health (FG-AI4H), which aims to establish a standardized assessment framework for evaluating and benchmarking AI solutions for health.
AI4Healthcare: This website by the AI4Healthcare initiative provides a platform for connecting and collaborating with AI experts, healthcare professionals, and patients to co-create and co-evaluate AI solutions for health.

June 28 2023

Unleashing the Power of Artificial Intelligence in Healthcare: Revolutionising Patient Care – Part 1

Raphael Iloh Artificial Intelligence, Business Strategy, Cyber Security, Healthcare, Leadership, Risk Management, Security Risks, Security Strategy, Third-Party Risk Management advancedmedicine, ai, aihealthcare, artificialintelligence, changeculture, compliance, cybersecurity, digitalhealth, generativeai, healthcare, innovation, leadership, machinelearning, patientcare, privacy, technology, unbiasedmedicine

In a previous post, we discussed possible cybersecurity trends and predictions for 2023. Today, I thought we’d embark on a journey into the realm of Artificial Intelligence (AI) in healthcare. So, join me, if you may, as we explore the applications, benefits, challenges, and ethical considerations surrounding this groundbreaking yet evolving technology, and what are the future directions of AI-augmented healthcare systems. We’ll uncover the potential of AI to revolutionize the delivery of healthcare services, transcending boundaries and ushering in a new era of improved patient outcomes and innovation.

AI is not a new concept, but it has gained a lot of momentum and attention in recent years. AI is the ability of machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. It’s probably been contemplated in some quarters, that AI can also enhance or possibly surpass human capabilities in some domains, such as vision, speech, and natural language.

Understanding Artificial Intelligence in Healthcare

AI in healthcare is the use of machine-learning algorithms and software, or artificial intelligence, to mimic human cognition in the analysis, presentation, and comprehension of complex medical and healthcare data, or to exceed human capabilities by providing new ways to diagnose, treat, or prevent disease.

AI in healthcare can be classified into three main types:

Machine learning (ML): This is the process of training machines to learn from data and make predictions or decisions based on patterns or rules. ML can be further divided into supervised learning (where the machine learns from labelled data), unsupervised learning (where the machine learns from unlabelled data), and reinforced learning (where the machine learns from feedback or rewards).

Natural language processing (NLP): This is the process of enabling machines to understand and generate natural language, such as text or speech. NLP can be used for tasks such as information extraction, sentiment analysis, text summarization, question answering, and conversational agents.

Computer vision (CV): This is the process of enabling machines to perceive and interpret visual information, such as images or videos. CV can be used for tasks such as face recognition, object detection, scene understanding, medical imaging analysis, and gesture recognition.

AI in healthcare can also involve other technologies, such as robotics (the use of machines to perform physical tasks), the Internet of Things (the interconnection of devices and sensors that collect and exchange data), blockchain (the use of distributed ledgers to store and verify transactions), and cloud computing (the use of remote servers to store and process data).

Applications of AI in Healthcare

AI has many applications in various fields and industries, but one of the most promising and impactful areas is healthcare and medicine. AI can help improve the delivery and quality of health services, advance medical research and innovation, as well as empower patients and communities.

Let us delve into the remarkable applications of AI in the healthcare domain, where its potential knows no bounds.

Diagnosis and medical imaging: AI can help improve the speed and accuracy of diagnosis and screening for diseases by analysing various types of data, such as symptoms, medical history, lab tests, genetic information, and imaging scans. For instance, AI can help detect skin cancer by comparing images of skin lesions with a database of known cases or diagnose diabetic retinopathy by analysing retinal photographs for signs of damage.
By augmenting human expertise, AI can enhance diagnostic accuracy, leading to earlier detection of diseases such as cancer. Case studies have shown remarkable success in AI-assisted radiology, revolutionizing the way we identify early-stage cancers and potentially saving countless lives.
Predictive analytics and personalised treatment: AI can assist with clinical care by providing recommendations or guidance for optimal treatment plans, dosages, or procedures based on patient characteristics, preferences, and outcomes. For example, AI can help optimize radiation therapy for cancer patients by generating personalized plans that minimize damage to healthy tissues or assist surgeons with robotic tools that enhance precision and control.
Research: AI can help advance medical research and innovation by discovering new insights, hypotheses, or solutions from large and complex datasets, such as clinical trials, genomics, or population health. For example, AI can help design new drugs by screening millions of molecules for potential efficacy and safety or find new links between genetic codes and diseases by analysing patterns across genomes.
Public health: AI can help improve public health interventions, such as disease surveillance, outbreak response, and health systems management by monitoring, predicting, and responding to health events or trends at local or global scales. For example, AI can help track the spread of infectious diseases by analysing data from social media, news sources, or mobile devices, or optimize the allocation of health resources by forecasting demand and supply based on historical data and real-time information.
Administration and virtual assistants: AI can help improve the efficiency and performance of administrative and operational workflows, processes, and financial operations by automating or streamlining tasks that are repetitive, time-consuming, or susceptible to errors. For example, AI can help automate the processing of insurance claims or billing by extracting and validating information from documents or images as well as reduce fraud and waste by detecting anomalies or inconsistencies in health data or transactions.

Benefits of AI in Healthcare

AI for health has the potential to bring positive impacts to various stakeholders, such as patients, providers, researchers, policymakers, and society at large. Here are some benefits of AI in healthcare:

Improve accuracy, speed, and scalability: AI can help improve the quality and reliability of health services by reducing errors, delays, and variability that may arise from human factors, such as fatigue, bias, or inconsistency. AI can also help scale up health services by reaching more people or places that may have limited access to human expertise or resources.
Reduce costs and increase efficiency: AI can help reduce the costs and inefficiencies of health systems by optimizing the use of assets and resources, such as equipment, staff, or facilities. AI can also help prevent or minimize errors or adverse events that may result from human mistakes or malpractice, such as misdiagnosis, medication errors, or surgical complications.
Enable personalised and preventive care: AI can help tailor health services to the individual needs and preferences of each patient by considering their respective characteristics, such as genetics, lifestyle, or environment. AI can also help prevent or delay the onset or progression of diseases by identifying risk factors or early signs of illness and providing timely interventions or recommendations.
Empower patients and communities: AI can help empower patients to take greater control of their respective health care and better understand their evolving needs by providing them with access to information, education, or support. AI can also help engage and mobilize communities to participate in health promotion or protection activities by providing them with feedback, incentives, or social networks.

The greatest opportunity offered by AI is not reducing errors or workloads, or even curing cancer: it is the opportunity to restore the precious and time-honoured connection and trust.
— Eric Topol, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again

Conclusion:

Without any doubt, the fusion of AI and healthcare offers unparalleled potential for improved patient outcomes, operational efficiency, and personalized care. However, whilst the promises of AI in healthcare are immense, AI for health also poses significant challenges and risks for health systems, such as ethical, social, and technical issues.

In the next article in the series, we’ll delve into some of these challenges and proffer possible solutions to these challenges to ensure responsible AI adoption in healthcare.

Arrivederci; take care, see you around soon.

In the meantime, if you’re interested in learning more about AI in healthcare, you can check out these resources:

IBM: This website provides an overview of AI in healthcare, its benefits, use cases, solutions, and resources.
Wikipedia: This article provides a comprehensive introduction to AI in healthcare, its history, applications, challenges, ethics, and future.

top cybersecurity risks trends and predictions for 2023

December 31 2022

Top Cybersecurity Trends and Predictions for 2023

Raphael Iloh Cyber Security, Risk Assessment, Risk Management, Security Risks, Security Strategy, Third-Party Risk Management compliance, cybersecurity, data breach, infosecurity, predictions, resilience, riskmanagement, risks, security, security strategy

Without a doubt, 2022 has been such an eventful year in the world of cybersecurity. There were over 2.8 billion reported cases of malware attacks worldwide and over 236 million reported cases of ransomware attacks just in the first half of the year.

In 2022, the government of Costa Rica declared a state of emergency and Toyota was forced to shut its 14 factories in Japan, following different and several cyberattacks.

As we enter the last few hours of 2022 and look forward to 2023, cybersecurity remains top of the agenda for the leaders of several businesses and organizations worldwide.

It is, therefore, natural to start thinking about what the next year might bring in terms of cybersecurity trends and predictions, and help inform decisions on information security strategies and budgets.

Here are my top 10 cybersecurity trends and predictions for 2023:

Ransomware Attacks

Ransomware attacks, in which hackers encrypt a victim’s data and demand payment to decrypt it, have been a major problem in recent years. These attacks are likely to continue in 2023, as hackers find new ways to target businesses, organizations and individuals across different spectrums in different societies and cultures.

Remote Work Security

The shift towards remote work, accelerated by the COVID-19 pandemic, has created an increased need for secure remote access solutions. The nature of remote work is changing and more organizations are adopting policies and environments that allow their employees to carry out their respective tasks remotely more effectively.

In 2023, we can expect to see a continued focus on this area, as organizations look for ways to protect their networks and data while employees are working remotely.

Further developments in this area include the adoption of virtual private networks (VPNs) and other secure remote access technologies, as well as the implementation of strong authentication protocols and the use of multi-factor authentication.

Another major trend in this space is something known as Decentralized Security; a comprehensive network of proactive and reactive defenses with built-in machine learning features that monitor endpoints, identities, and access regardless of who the users are, what they do, or wherever they may be connected from.

Supply Chain Attacks

Supply chain attacks involve compromising the security of a third-party vendor or supplier to gain access to an organization’s systems or data. These attacks can be difficult to detect and prevent because they usually do not involve any direct interaction with the target organization.

Organizations can establish steps to mitigate against such attacks including implementing secure supply chain practices, conducting thorough random checks on their suppliers, and implementing incident response plans.

A recent policy statement published by the Bank of England outlines regulations that affect financial institutions regarding outsourcing and third-party risk management.

New Technologies & More Attack Vectors

As new technologies emerge, they will also bring new attack vectors for hackers to exploit. In 2023, we may see an increase in attacks targeting the internet of things (IoT), as well as attacks targeting emerging technologies such as 5G networks and quantum computers.

Artificial Intelligence and Machine Learning

Artificial intelligence (AI) and Machine Learning (ML) have already started to play a significant role in cybersecurity, and this is likely to continue in 2023. These technologies can be used to analyze large amounts of data and identify patterns and anomalies that might indicate a security threat.

One example of this is the use of AI and machine learning to analyze log data and identify unusual activity that might indicate a cyberattack. This can help organizations respond more quickly to threats and minimize the damage caused by an attack.

Regulation and Compliance Requirements

As cybersecurity threats continue to evolve and become more sophisticated, we are likely to see increased regulation and compliance requirements in the coming year. This may include new laws and regulations that require organizations to implement certain security measures, as well as increased penalties for organizations that fail to meet these requirements.

Last year, I wrote an article about the Digital Operational Resilience Act (DORA) regulation proposed by
the European Union (EU).

With DORA, the EU aims to harmonize and improve risk management and operational resilience within the financial sector across the region by addressing many of the issues that concern leadership, governance, and continued operations through a severe operations disruption as well as establishing an oversight framework for managing ICT critical third-party providers (CTPPs).

The Council of the European Union (i.e., EU Council) recently adopted DORA as policy across the region.

Evolution of Cyber Threats

Cyber threats are constantly evolving, and we can expect to see new types of attacks and tactics in 2023. As hackers become more sophisticated, they will continue to find new ways to target organizations and individuals.

To protect against these evolving threats, it will be important for organizations to stay informed about the latest developments in cybersecurity and to implement effective security measures. This may involve investing in new technologies and training employees to recognize and respond to potential threats.

Cloud Security Solutions

The use of cloud-based security solutions is likely to increase in 2023, as organizations look for ways to protect their data and systems in the cloud. This may include the use of Cloud Access Security Broker (CASB) services and other cloud security technologies.

Zero-Trust Security Models

Zero-trust security models, which assume that all users and devices are untrusted until proven otherwise, are likely to become more popular in 2023. These models can help organizations protect against insider threats and ensure that their networks and systems are secure.

We can expect more security products and services to be compliant with zero-trust models, satisfying all seven tents of the NIST 800-207 model on zero-trust, as an example.

Data Privacy and Protection

As more data is collected and stored online, the protection of personal and sensitive information will continue to be a major concern in 2023. Organizations will need to implement strong data privacy measures to ensure that they comply with applicable laws and regulations as well as protect against data breaches.

“How do we effectively protect our consumers’ information from unauthorized access, use, and abuse?” This is just one of many pertinent questions that information security and risk leaders must anticipate for the future and plan accordingly.

Cybersecurity Insurance

According to a recent report, the global cybersecurity insurance market size is expected to reach US$32.6 billion by 2028.

As the risks of cyberattacks continue to grow, we can expect to see an increase in the use of cybersecurity insurance in 2023. This type of insurance can helps organizations protect against the financial impacts of a cyberattack and ensure that they have the resources to recover from an incident.

We’re falling into this old habit of trying to treat everything the same as we did in the past… This simply cannot continue. We need to make sure that we are evolving our thinking, our philosophy, our program, and our architecture.
— Sam Olyaei, Gartner Analyst

In conclusion, 2023 is likely to see an increase in supply chain attacks, state-sponsored cyberattacks, a continued focus on the security of remote work, the emergence of new technologies and attack vectors, and the growth of ransomware attacks. However, it will also be a year for some organizations to derive benefits from their investments, preparedness, and innovations in information security and regulatory compliance best practices.

Why Cyber Kill Chain not Sufficient to Protect Your Organization

July 3 2022

Why The Cyber Kill Chain Is Not Sufficient to Effectively Protect Your Organization

Raphael Iloh Cyber Security, Infosec, Risk Management, Security Architecture, Security Risks, Security Strategy advanced persistent threat, apt, business continuity, cyberattacks, cybersecurity, disaster recovery, framework, governance, infosecurity, leadership, riskmanagement, risks

An epochal shift during the 21st century has led us to enter a new era of technological advancements, where cyber security has become vital in keeping an organization and business secure.

The rise of computers, telecommunications and the internet had opened the doors for cyberterrorism. Cyberattacks had become so rampant that they started to become a threat to the economy. Cybercriminals and hackers have also evolved their digital skills in stealing and destroying other businesses by breaching information security.

Having an effective security system to protect your organization is your best defense against cybersecurity threats. It does not only protect your business but your consumers and employees as well.

Investing in an efficient cybersecurity plan promotes risk management for monetary and reputational damage and ensures data integrity and confidentiality within your organization.

Ignoring cybersecurity is a grieve and an expensive mistake to make. Though it may not eliminate the risk of cyberattacks, a layered security approach can withstand cyber intrusion and assaults.

Lockheed Martin Cyber Kill Chain Framework

The Cyber Kill Chain is a stage-based framework (or methodology, if you like) originally developed by Lockheed Martin which traces the stages of cyberattacks. An adaptation of an established military defense operation, it is a part of their Intelligence Driven Defense Model that identifies vulnerabilities and prevent cyber intrusion activities.

This framework is named “Kill Chain” as it was adapted from a military term related to an attack’s structure. By stopping the attacker at any stage during the assault can break the chain of attack! The adversary must completely advance through all the stages to succeed. Each stage of intrusion will give us the chance to know more about the attacker and use their tenacity as our leverage.

The Kill Chain Framework works in 7 stages:

Reconnaissance – The step where the targets are identified. Adversaries plans and research their target organizations. These intruders will use automated scanners to find weak points in the system. They could scan firewalls to create a point of entry in the system. Detecting the intruders during reconnaissance could be challenging, but it could help reveal the attackers’ criminal intents.
Weaponization – The adversaries start staging their operation. After finding security vulnerabilities in the system, these attackers will develop malware. If their target is document-based, they produce a “decoy” file to present to the victim. They weaponize malware based on the attack’s intention. This is also the stage where adversaries could find ways to reduce their chances of being detected. The defender will not detect weaponization as it happens, but they can figure out the intent by investigating malware artifacts.
Delivery – The adversaries start to launch their operations. The attackers will start sending the malware to the defenders. They will deliver the weapon through email phishing or a removable/portable device. This is a vital stage for the defenders. Blocking the operation should be prioritized at this point. This can be done if the delivery medium is analyzed or targeted servers are detected.
Exploitation – Advancing to this stage is when the attackers start to gain access to their victims. The malicious malware was delivered and breached the secured parameter. Opening a phishing email attachment or clicking on a malicious link has triggered the “zero-day”, a phrase that refers to the exploit code. At this rate, custom capabilities are crucial to stop zero-day exploits. But traditional hardening measures could also help in adding resiliency to the security.
Installation – The hacker, had already established a beachhead at the victim. The malware has installed a backdoor that will serve as a point of entry for the intruder. Some adversaries would ensure that the malware looks like a regular part of the installed operating system. In this stage, it is important to stop the attack by using systems such as the Host-Based Intrusion Prevention System (HIPS). It can alert or block common installation paths.
Command and Control (C2) – The adversaries gain control of the system’s network. The malware has opened a channel of command to remotely manipulate the victim. They can gain access to secure and confidential accounts and could attempt damaging attacks. This stage is the defender’s last chance to block the attack. And this can be done by blocking the C2 channel. This will stop the adversaries from issuing a command to prevent further damage.
Action on Objectives – The adversaries have reached their goals-the stage where the hackers have successfully extracted their needed data from the system. They gained the power to damage further, such as collecting user credentials, destroying the system, or overwriting and corrupting the data. The longer the hacker has access to CKC7, the greater the impact of the damage. This stage could be detected as soon as possible using forensic evidence and network packet capture.

cyber kill chain model

Key Elements of the Cyber Kill Chain:

The Cyber Kills chain was designed to assist companies in developing in-depth strategies for defense. By mapping out the steps that the hackers take to complete a cyberattack, organizations would be able to combat persistent cyber threats.

Since the Cyber Kill was derived from a military model, the main elements of this framework are established to identify adversaries, prepare for an attack, engage, and destroy a target. It can quickly identify and recognize social engineering, insider threats and innovative attacks.

Drawbacks of Kill Chain Framework

The Cyber kill chain is modelled to respond to pre-determined attack sequences. It has been universally adopted for cybersecurity. But like any other model, it is not perfect and has its fundamental flaws.

The model assumes a perimeter focus defense where the main resistance is a firewall. It fails to cover other internal attacks and cyberattack vector paths.
Cyber Kill Chain framework’s phase sequence cannot precisely block all attacks. Most of its phases can be easily bypassed.
The framework only focuses on blocking an attack but fails to define what to do after the adversaries successfully breaches the system.
Once the adversary was able to penetrate the victim’s system, the framework’s timing of the attack in every phase was inconsistent. Adversaries could easily stay dormant for a longer period while they wait for the opportunity to launch their final phase of attack without being detected.

Teams that say their cybersecurity is really good are the ones to worry about. After our breach, the most difficult issue was deciding when it was safe enough to come back online. I learned that really smart engineers can talk English, under extreme pressure.
— Dame Dido Harding, former CEO of TalkTalk

Other Frameworks with Similar Objectives Compared to the Cyber Kill Chain

MITRE ATT&CK vs Cyber Kill Chain

ATT&CK is an acronym that stands for Tactics, Techniques, and Common Knowledge.

The MITRE ATT&CK framework was designed based on observations in the real world. It reflects the different phases of an intruder’s attack lifecycle and the target platforms.

One could argue that there are Cyber Kill Chain and MITRE ATT&CK both share common views and understanding of cyberattacks i.e., most cyberattacks involve adversaries breaking into networks, avoiding getting detected, stealing as much data as they possibly can, interrupting as much network operations as they possibly can, getting out as quietly and stealthily as they got in, making hidden backdoor access available if they ever need to return, etc.

However, compared to Cyber Kill Chain, the Mitre ATT&CK framework maintains a matrix model that has more in-depth details on how the adversary will attack in each stage. Also, Cyber Kill Chain fail to factor in the different techniques and tactics of a cloud-native attack.

The Cyber Kill assumes that the attackers will deliver malware to a target environment but ATT&CK assumes that the adversaries may very well change their goals/objectives mid-way through an attack especially when the success of the attack appears either easier or more difficult than they had initially planned.

Yes, one could argue that the MITRE ATT&CK framework uses Situational Crime Prevention (SCP) techniques, a set of techniques which assumes that the goals/objectives of most adversaries are not linear but influenced/informed by opportunities, constraints, limitations, resistance, and situations presented to them by their targets during the execution of attacks.

Google BeyondCorp vs Cyber Kill Chain

BeyondCorp is an implementation of a zero-trust security concept that creates a zero-trust network. Designed to provide end-to-end real-time protection and platform security. It has embedded data built into the Chrome browser to prevent malware infection from networks and provide phishing-resistant authentication.

Unlike the Cyber Kill Chain framework, Google BeyondCorp “shifts access control from the traditional network perimeter to individual devices”. Its zero-trust access approach users to securely work with untrusted networks even if they are not using a client-side VPN.

NIST Cyber Security Framework (NIST CSF)

The National Institute for Standards & Technology (NIST) Cyber Security Framework (CSF) provides a set of structured standards and measurements for cybersecurity. The framework sets out “standards, guidelines, and best practices to manage cybersecurity-related risks.”

But the downside of the framework is that its 5 categories/elements i.e., Protect, Identify, Detect, Respond and Recover; fail to directly outline how it can dissect a cyberattack incident. It also fails to supply analytic markers to test the detection.

Nevertheless, the descriptive (and not prescriptive) nature of the NIST CSF has made it seem “business-friendly” and therefore, made it possible for the framework to be adopted by businesses and organizations of all sizes and across several industries, particularly organizations in industries that are guided by regulary controls and compliance requirements where industry-uniqueness and specificities are considered important.

data breach

In conclusion, there is no one defense framework or set of techniques that could be considered all-in-one sufficient for all cybersecurity defense requirements.

In a previous article, I had looked at how the proposed Digital Operational Resilience Act (DORA) could impact businesses and organizations once ratified and signed into law.

Given the significant penalties that would be imposed for non-compliance with DORA directives, it is perhaps reasonable to envisage that DORA could eventually have similar, if not greater, impacts in both the UK and the EU region as did GDPR, albeit with very different objectives.

Whilst some of these defense techniques may excel in certain aspects of information security, many of them are complimentary to each other and bring different or much enriched strengths to the conversation.

Risk Management

Understanding the Metaverse: Unravelling the Infinite

Cybersecurity Challenges and Risks in the Metaverse

Cybersecurity Solutions for the Metaverse: Thriving amidst Adversity

Cybersecurity Opportunities in the Metaverse

Final thoughts

Understanding False Assurance

Causes of False Assurance

Implications of False Assurance

Mitigating False Assurance

Closing thoughts

Further reading

Define your vision and strategy for cybersecurity

Build your team and empower them

Develop policies, standards, and procedures for cybersecurity

Implement controls and measures for cybersecurity

Review risks and opportunities for cybersecurity

Engage stakeholders and partners for cybersecurity

Final thoughts

Further reading

The Role of Leadership in Cybersecurity Governance

Understanding the Complex Challenges

Conclusion

A holistic approach to C-SCRM

Generative AI for C-SCRM

A reinforced and sturdy C-SCRM

Conclusion

What’s Cybersecurity Supply Chain Risk Management?

How to Mitigate C-SCRM Risks?

Conclusion

Challenges and Ethical Considerations

Overcoming Challenges and Ensuring Responsible AI Adoption

The Future of AI in Healthcare

Conclusion

Understanding Artificial Intelligence in Healthcare

Applications of AI in Healthcare

Benefits of AI in Healthcare

Conclusion:

Ransomware Attacks

Remote Work Security

Supply Chain Attacks

New Technologies & More Attack Vectors

Artificial Intelligence and Machine Learning

Regulation and Compliance Requirements

Evolution of Cyber Threats

Cloud Security Solutions

Zero-Trust Security Models

Data Privacy and Protection

Cybersecurity Insurance

Lockheed Martin Cyber Kill Chain Framework

The Kill Chain Framework works in 7 stages:

Key Elements of the Cyber Kill Chain:

Drawbacks of Kill Chain Framework

Other Frameworks with Similar Objectives Compared to the Cyber Kill Chain

MITRE ATT&CK vs Cyber Kill Chain

Google BeyondCorp vs Cyber Kill Chain

NIST Cyber Security Framework (NIST CSF)

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