IWAPS

International Workshop on Advances on Security and Privacy Technologies and Solutions

Workshop Chairs

→ Christos Xenakis
→ Aristeidis Farao
→ Apostolis Zarras

Detail 01/04

IWAPS 2026 to be held in the conjunction with the 19th International Conference on Availability, Reliability and Security

IWAPS 2026 aims to advance secure, privacy-preserving, and trustworthy AI systems by fostering research and practical solutions for next-generation cyber-resilient architectures. The workshop addresses a broad spectrum of topics including advanced cyber-defense strategies, large-scale data analytics and fusion platforms, secure protocols and services, adversarial robustness, federated learning, confidential computation, differential privacy, trustworthy model deployment, and privacy-enhancing technologies for IoT and cyber-physical systems. It also explicitly encourages multidisciplinary work at the intersection of technology, policy, regulation, ethics, human-centered security, and societal impact in order to shape the future roadmap for secure and trustworthy AI systems.

Topics of interest include, but are not limited to 02/04

Adversarial machine learning: attacks, defenses, and robustness
Protection mechanisms against adversarial ML attacks
Threat and attack models for adversarial AI systems
Deep learning for security and privacy
ML-based intrusion, anomaly, and malware detection
ML techniques for deep packet inspection
ML-assisted analysis and verification of cryptographic protocols
Privacy-preserving optimization and machine learning
Trust frameworks and trust management models for IoT systems
Threat modeling and attack surfaces in IoT environments
End-to-end security models for IoT and cyber-physical systems
Privacy-preserving technologies and solutions for IoT platforms
Distributed and federated privacy-preserving algorithms
Self sovereign identity
Privacy policies, regulatory compliance, and legal challenges
Governance models for trustworthy and accountable AI
Legal and policy aspects of privacy-preserving technologies
Ethical-by-design and policy-aware AI systems
Cybersecurity risk management and assessment
Security controls optimization and budget allocation
Security economics and investments in cyber defense
Human rights, surveillance, and societal implications of privacy technologies
Applications of privacy-preserving AI systems
End-to-end secure system design and evaluation
ML for automated software testing and security validation
Benchmarking privacy and security technologies in real-world settings
Privacy-preserving and ML-based data analytics
AI/ML techniques for cyber threat intelligence
Automated attack mitigation and response strategies
Game-theoretic models for attack and defense strategies
Architectures and protocols for scalable, secure, and privacy-enhancing technologies
Quantum cryptography
Cryptographic approaches for security and privacy
Differential privacy: theory, mechanisms, and applications
Privacy-enhancing and anonymization techniques
Attacks on data privacy and inference risks
Secure and confidential computation
Privacy-preserving security and privacy policies
Privacy-preserving test cases, datasets, and benchmarks
ML-based prediction of the weakest link in system architectures
Human factors in adversarial AI and cybersecurity
Ethical considerations in adversarial AI systems
Psychological, sociological, and anthropological aspects of usable security and privacy
Psychological manipulation and influence modeling using ML
ML techniques for predicting social engineering and manipulation attacks
Human firewall concepts and weakest-link analysis