Specific Challenge:
In order to minimise security risks, ICT systems need to integrate state-of-the-art approaches for security and privacy management in a holistic and dynamic way. Organisations must constantly forecast, monitor and update the security of their ICT systems, relying as appropriate on Artificial Intelligence and automation, and reducing the level of human intervention necessary.
Security threats to complex ICT infrastructures, which are multi-tier and interconnected, computing architectures, can have multi-faceted and cascading effects. Addressing such threats requires organisations to collaborate and seamlessly share information related to security and privacy management.
The increasing prevalence and sophistication of the Internet of Things (IoT) and Artificial Intelligence (AI) broadens the attack surface and the risk of propagation. This calls for tools to automatically monitor and mitigate security risks, including those related to data and algorithms. Moreover, storage and processing of data in different interconnected places may increase the dependency on trusted third parties to coordinate transactions.
Advanced security and privacy management approaches include designing, developing and testing: (i) security/privacy management systems based on AI, including highly-automated analysis tools, and deceptive technology and counter-evasion techniques without necessary human involvement; (ii) AI-based static, dynamic and behaviour-based attack detection, information-hiding, deceptive and self-healing techniques; (iii) immersive and highly realistic, pattern-driven modelling and simulation tools, supporting computer-aided security design and evaluation, cybersecurity/privacy training and testing; and (iv) real-time, dynamic, accountable and secure trust, identity and access management in order to ensure secure and privacy-enabling interoperability of devices and systems.
