This book is based on the best papers accepted for presentation at the AISMA-2026: International Workshop on Advanced Information Security Management and Applications, to be held on October 20–25, 2026, in Stavropol, Russia, and online.

The book compiles cutting-edge research on information security challenges and solutions, spanning the domains of artificial intelligence, cryptography, intrusion detection, and critical infrastructure protection. The scope of research methods presents original contributions, including mathematical models, formal behavioral analysis, and software implementations, related to the following topics: reinforcement learning and hybrid feature selection for intrusion detection, federated learning frameworks for privacy-preserving analytics, homomorphic encryption for computation on encrypted data, post-quantum cryptography based on modular codes and residue number systems, and blockchain security with quantum risk assessment.

In addition, the book explores the integration of security into cyber-physical systems, with papers addressing intelligent IoT frameworks for water quality monitoring and fish health detection, attack simulation on physical channels using educational testbeds, and security modeling for unmanned aircraft systems in civil aviation. The book also delves into human-centric and organizational aspects, including cognitive load analysis in cybersecurity, behavioral information security based on multimodal employee profiling, physician competence in digital health care, and an integrative review of cybersecurity strategies in education.

Furthermore, the book investigates emerging threats and defensive technologies, including deception technology management, prompt injection and context poisoning in RAG-enabled assistants, low-code/no-code automation for vulnerability management, and real-time wireless threat detection via SkySniff with dynamic risk assessment. Finally, the book provides insights into identity-aware SIEM-IAM correlation for false-positive reduction, semantic normalization for optical recognition channels, and two-contour methods for detecting compromise of AI models. The book is intended for readership specializing in information security management, applied cryptography, AI security, and the protection of critical information infrastructure.