- Track 1: Network Security: Intrusion detection, anomaly detection, malware analysis, AI-driven threat intelligence, secure network protocols, cloud/edge/IoT security, adversarial traffic analysis, AI-assisted red-team operations.
- Track 2: Information Security: AI-based data protection, cryptography and key management, IAM, digital forensics, privacy-preserving ML, secure data pipelines, risk modelling, automated incident response.
- Track 3: Software Security: Vulnerability detection using AI, automated code review, secure DevOps, secure SDLC, fuzzing, static/dynamic analysis, supply-chain security, GenAI security risks in coding tools.
- Track 4: Security of AI: Adversarial ML, model extraction/inversion, data poisoning, watermarking, secure training pipelines, LLM robustness, federated learning security, trustworthy AI deployment.
- Track 5: AI Ethics and Security Compliance: Responsible AI, explainability, bias and fairness audits, governance frameworks, regulatory compliance (EU AI Act, IndiaAI), societal impacts, accountability mechanisms
- Track 6: AI and Security in Defense: AI-Driven Threat Detection and Predictive Intelligence, Autonomous Systems Security (UAVs, UGVs, USVs), Adversarial Machine Learning in Military Environments, Cyber Defense Using AI for Critical Defense Infrastructure, Explainable AI (XAI) for Defense Decision-Making, AI for Surveillance, ISR, and Battlefield Awareness, Secure Federated and Distributed Learning for Defense Networks, AI-Enabled Electronic Warfare and Signal Intelligence (SIGINT)
