AI and Cybersecurity [Part 2]: Digitalisation and Testing

Digitalisation continues to drive innovation and growth. But wherever there is progress, risks are never far away and require constant vigilance. The threat of cyber attacks in particular is forcing companies to scrutinise their security solutions on a regular basis. At the same time, companies that rely on AI-supported threat detection and modern cybersecurity can secure a decisive edge. The new ISO/IEC 42001:2023 standard provides a comprehensive framework for ensuring protections and the ethical use of artificial intelligence. In the second part of our blog series, we’ll show you which technologies you can use to leverage this transformative potential securely and ethically.

The transformative power of digitalisation

Digitalisation is the engine for innovation and growth. Digitalisation enables companies to develop new business models, tap into new markets and continuously optimise their products and services. Just think about the flexibility and scalability that digital technologies offer: cloud computing and mobile solutions enable people to work anywhere and at any time, while also collaborating and communicating efficiently.

Industry 4.0: Companies are optimising their production processes and improving efficiency by networking machines and using the IoT (Internet of Things).

E-commerce: Enables companies to create online shops quickly and cost-effectively so they can sell their products worldwide.

xTech digitalised services: Existing processes and services in traditional industries are being digitalised to simplify them, optimise the user experience and increase efficiency. Examples include health (HealthTech), financial services (FinTech) and education (EdTech).

At the same time, digitalisation also poses challenges, so it’s crucial to get the balance right between potential and risk. This may be necessary for instance if excessive dependence on digital technologies is resulting in operational disruptions, or systems are failing or are even subject to attacks. Emergency plans, a strategy for business continuity management (BCM) and backup systems are critical in this context. Integrating new digital solutions into existing systems can be complex and requires a scalable and adaptable IT infrastructure.

Cybersecurity: guardians of the digital world

In an increasingly networked world, cybersecurity is critical. Modern security technologies (with and without the use of AI) can recognise threats at an early stage and ward them off before they cause any damage. This is not only a protective shield, but also generates trust. Companies that invest in their IT security gain the trust of their customers and business partners – an invaluable competitive advantage.

• Zero Trust Security – where every interaction inside and outside the network is considered potentially insecure – is gaining in importance. Read more about Zero Trust 2.0 in our dedicated blog series.
• SOC/CDC: Our cyber defence services are being continuously optimised through the use of AI and ML (machine learning).
• Firewalling and micro-segmentation: Insights from actual attacks are applied to self-learning security rules, reducing the attack surface and increasing security.
• AI supported threat detection to recognise unusual activities in real time and respond with situation-based security processes before damage occurs.

The need for AI arises from the increasingly complex threat situation. As cyber criminals are increasingly turning to advanced techniques, companies are forced to respond with defensive measures that are at least as innovative.

Many of the solutions used in the cybersecurity sector already rely on AI support, virus scanners, mail filtering, IDS and XDR, AI-generated user-specific phishing simulations right up to real-time monitoring using SIEM and SOC/CDC with automated playbooks.

AI gap analysis (AI readiness)

To obtain a comprehensive picture of the maturity level of your cybersecurity measures with regard to your AI stack, we recommend a review using an independent AI gap analysis. The result helps you to increase AI maturity in a prioritised and risk-based manner and thus protect your digital resources and sensitive information against cyber threats.

The aim is to promote a systematic approach to the management of sensitive data that takes both technical and organisational aspects into account. The security-related challenges, data-protection issues, compliance requirements and ethical aspects that arise when applying and using artificial intelligence in cloud environments are identified, prioritised and addressed with suitable risk mitigation measures.

The ISO/IEC 42001:2023 standard builds on the foundations of ISO 27001:2022 and expands it to include specific requirements and measures that meet the current threats in the area of AI management. It can be ideally extended with other frameworks such as Cloud Security Alliance (CSA) Responsible AI in a Dynamic Regulatory Environment (CSA Responsible AI), NIST AI RMF (later possibly NIST ARIA) or BSI AIC4.

Specific requirements of the ISO/IEC 42001 standard

Risk assessment and risk management: The standard emphasises the need for a thorough risk assessment to identify and evaluate potential threats. Appropriate security measures must be developed and implemented on this basis.

Politics and accountability: Organisations must develop clear security guidelines and define responsibilities. This also includes training employees so that everyone involved develops an awareness of cybersecurity and understands their role in the security structure.

Technical safety measures: Specific measures include the implementation of encryption techniques and access controls, firewalls etc. to prevent unauthorised access and data loss.

Monitoring and improvement: The standard requires continuous monitoring and regular audits of safety measures to check their effectiveness and make any necessary adjustments.

Response to security incidents: An effective security incident response plan is essential. ISO/IEC 42001 emphasises the importance of a rapid and coordinated response to minimise damage and prevent future incidents.

Advantages of ISO/IEC 42001:2023

Companies can use the recommended controls to significantly optimise their security situation, strengthen the trust of customers and partners and ensure better legal compliance. The aim is to establish a culture of continuous improvement and proactive safety management.

Overall, ISO/IEC 42001 is an essential addition to existing cybersecurity and risk management standards and provides organisations with a clear framework to effectively address the growing cyber threats and ensure the safe, ethical and efficient use of AI in cloud environments.

Based on frameworks such as the ISO/IEC 42001:2023 standard, AI gap analysis helps you to develop suitable measures for the secure use of your AI stacks.

AI and cybersecurity, the three-part blog series

Expand your expertise in the safe and secure use of AI technologies as part of your digital risk management. We’ll accompany you on this journey with our “AI and cybersecurity” blog series. 

• AI and cybersecurity part 1: Fine-tuning between potential and risk
• AI and cybersecurity part 2: Digitalisation and testing

The third part on the topic of “Challenges of AI-as-a-Service” will be published soon. Subscribe to our blog update to receive the third part directly in your mailbox.

• AI and Cybersecurity Part 3: Challenges of AI-as-a-Service 
  
  

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