Computational Intelligence in Security for Information Systems
Description
This book constitutes the refereed proceedings of the 19th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2026, held in Marbella, Spain, during June 18-19, 2026.
The 23 full papers included in this volume were carefully reviewed and selected from 49 submissions. The papers cover the following topical sections: Hybrid Security Analytics; Secure AI, and Cryptography & Software Assurance. The papers also include the special session: Artificial Intelligence for Protecting the Internet of Things (AIP-IoT).
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Content
.- Hybrid Security Analytics
.- Blink-and-You'll-Miss-It: Micro-Expressions as a Deepfake Detection Add-On.
.- Rethinking Synthetic Oversampling for Intrusion Detection: When Similarity Hurts Performance.
.- Deep Sets for Network Flow Anomaly Detection under a Multiple Instance Learning Framework.
.- Explainable Mixer-Like Behavior Detection in Bitcoin via Transaction-Level Heuristics.
.- Unsupervised Temporal Analysis of Bitcoin Transaction Networks Using Topological Drift.
.- Secure AI, Cryptography & Software Assurance.
.- Securing LLM Agents in Production: Threat Models, Defenses, and Operational Trade-Offs.
.- Towards Post-Quantum Security: An Architecture Proposal for Securing Cyber-Physical Systems Telemetry.
.- Analysis and Comparison of Fully Homomorphic Encryption Approaches over Integers.
.- Tailored Limb Counts, Faster Arithmetic: Improved TMVP Decompositions for Curve5453 and Curve6071.
.- Guarding Pointer Arithmetic in LLVM IR: A Lightweight Static Analysis Pass.
.- Special Session: Artificial Intelligence for Protecting the Internet of Things (AIP-IoT).
.- Explainable ANFIS-Based DDoS Detection for Edge IIoT.
.- Cybersecurity Audit of the Unitree Go2 Quadruped Robot.
.- Real-time identification and evaluation of DoS attacks for embedded systems.
.- A Hybrid Forensic Investigation Framework: Mobile Malware, Memory Threats, and Deepfake Detection.
.- Comparison of Temporal Flow Aggregation Strategies for Transformer-Based Network Intrusion Detection.
.- Vulnerability Assessment of IoT Ecosystems: A Case Study on Replay Attacks in Wi-Fi Enabled Smart Actuators.
.- Framework Design for Privacy Preserving Machine Learning in a 6G Vehicular Network.
.- Machine Learning Validation of a Flow-Based IoT Cyberattack Dataset.
.- Identification of relevant digital forensic traces using time window aggregation and hierarchical clustering
.- Cross-Dataset Generalization of Random Forest Classification Models for IoT Network Traffic Attack Detection.
.- Mixed-Traffic IoT Windows as Flow Sequences: A Transformer-Based Multi-Label IDS.
.- Anomaly Detection Through Quantum Annealing-Driven Feature Selection.
.- Autonomous Edge Cybersecurity: LLM-Guided Q-Learning for Resilient Device Control.