Artificial Intelligence for Cybersecurity applications

Expected Outcome

Proposals are expected to contribute to one or more of the following:

• AI-driven solutions for real-time cyber threat detection;
• Advanced adaptive AI systems that evolve with dynamic cybersecurity challenges;
• Contribute to drastically reduce reaction time for the recovery of systems.

Scope

Artificial Intelligence is increasingly utilised in cybersecurity for threat detection, incident response, and adaptive defence mechanisms. However, AI-driven systems themselves are susceptible to adversarial manipulation and bias. This topic aims to advance AI-based cybersecurity applications while ensuring that AI-driven solutions remain resilient, transparent, and compliant with regulatory frameworks such as the AI Act. In this context, the topic explores the role of all types of AI, including generative AI, in cybersecurity applications, including automated threat detection, adaptive cyber defence, and AI-driven cyber threat intelligence. Proposals should develop solutions for trustworthy AI in cybersecurity contexts including addressing adversarial AI risks, in compliance with the provisions of the AI Act. The topic is expected to:

• Develop AI-driven solutions and tools for real-time cyber threat detection. Investigating novel machine learning techniques to detect anomalies, malicious activity, and AI-powered cyber threats in real time, improving situational awareness and response times.
• Develop adaptive AI systems capable of evolving with dynamic cybersecurity challenges. Exploring AI techniques that continuously learn from new cyber threats, adapting to emerging attack patterns, while maintaining robustness and explainability.
• Support the future enhancements of Security Operation Centres/Cyber Hubs. Developing AI-enhanced SOC frameworks that integrate predictive analytics, automation, and threat intelligence to strengthen proactive defence measures.