★ Introduction:

The fast advancement of Artificial Intelligence (AI) has significantly transformed various sectors, including cybersecurity. AI-driven tools enhance threat detection capabilities, automate incident responses, and bolster security frameworks. However, these advancements also present new challenges, including adversarial attacks and ethical concerns. This thematic track explores the intersection of AI and cybersecurity, offering a comprehensive discussion of the opportunities and threats. Moreover, inadequate cybersecurity measures to protect open-source AI models pose significant risks. Malicious actors can exploit vulnerabilities to manipulate, steal, or repurpose AI models for cyberattacks. Strengthening security protocols and implementing controlled dissemination of sensitive AI-related data and code can enable a more comprehensive assessment of security risks. This thematic track promotes a forum to discuss and present emergent topics, new projects, and ideas that examine the role of AI in enhancing cybersecurity mechanisms, identify potential threats posed by AI-driven cyberattacks, and explore ethical and legal considerations related to AI-driven cybersecurity.

★ List some of the topics, but are not limited to:

AI for Cybersecurity:
o The application of AI-driven solutions for threat detection and mitigation
o AI-powered anomaly detection and behavioural analysis
o Automated incident response systems
o AI in fraud detection and risk assessment
o Deepfake detection and generation techniques using AI

Cybersecurity for AI:
o Adversarial AI and its countermeasures
o Securing AI models and the privacy of data
o Explainability and trust in AI security applications
o Vulnerabilities in AI-based authentication systems

Ethical, Legal, and Policy Implications:
o Issues of bias and fairness within AI-driven cybersecurity systems
o Regulatory compliance and governance concerning AI in security
o Privacy-preserving techniques in AI
o The influence of AI on the cybersecurity workforce