Buch, Englisch, 783 Seiten, Format (B × H): 155 mm x 235 mm
28th International Conference, ICICS 2026, Fukui, Japan, October 27–30, 2026, Proceedings, Part III
Buch, Englisch, 783 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Computer Science
ISBN: 978-981-9268-36-8
Verlag: Springer
This set of volumes constitutes the refereed proceedings of 28th International Conference on Information and Communications Security, ICICS 2026, held in Fukui, Japan, during October 27–30, 2026.
The 148 full papers, 69 short papers and 16 poster papers presented in this book were carefully selected and reviewed from 499 submissions. The papers are organized in the following topical sections:
Part I: Full Papers — Cryptography and Secure Protocols.
Part II: Full Papers — Federated Learning, AI Model Security and Blockchain.
Part III: Full Papers — LLM Security, Software Security and Malware Analysis.
Part IV: Full Papers — Network, IoT, Hardware Security and Privacy.
Part V: Short Papers I — Cryptography, Secure Computation and Blockchain.
Part VI: Short Papers II — AI and Systems Security, and Posters.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Kryptographie, Datenverschlüsselung
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
Weitere Infos & Material
.- LLM and Agent Security .
.- EvoJudge: Confidence-Aware Rule Evolution for LLM Safety Auditing.
.- Patching the Ground: Representation-and-Generation Attacks on Dangerous-Object Grounding in MLLMs.
.- LLM-ETKG: Event-Centric and Evidence-Grounded Knowledge Graph Construction for Cyber Threat Intelligence.
.- Small Models, Big Variances: Unveiling the Impact of Execution Environments on SLMs’ Security.
.- SCOUT: Structural Coverage-Guided Diffusion for Testing Deep Classifiers.
.- WhalingX: A Concurrent Multi-Agent Penetration Testing Framework via BDI Cognition and Queuing Theory.
.- Cat-and-Mouse Game: AI Agents for URL Merging of Magnet Link Search Websites.
.- MIST: Malicious In-Distribution Stealth Attack on LLMs via Benign Interspersion.
.- When Facts Mislead: Defeating Search-Augmented Multi-Agent Debate via Factual Persuasion.
.- Structured Decomposition for Reliable LLM-Generated Access Control Policies.
.- SSIB: A Security-Centric Benchmark and Multi-Agent Framework for Detecting Stablecoin-Specific Vulnerabilities.
.- PriMedLLM: A TEE-Based Secure Mediation Framework for Privacy-Preserving LLM Training and Inference.
.- Composable CVE-Component Catalogs for Open-Source LLM-Driven Cyber Range Generation with Two-Tier Verification.
.- Vulnerability Detection and Fuzzing .
.- When Secrets Get Committed: The role of code platforms in avoiding secret leakage.
.- LAPSE: Guided Program-Slice Representations for Project-Level Vulnerability Triage
.- LAVD: Cross-Project Vulnerability Detection via Layer-Fading and Logical Alignment.
.- Exploring Function-Level Vulnerability Detection with Vulnerability Intelligence-Enhanced LLMs.
.- Hidden Ciphers and Where to Find Them: Static Discovery and Assessment of Cryptographic Assets in Software.
.- Edge-Aware Heterogeneous Graph Transformer for Source Code Vulnerability Detection.
.- Toward Comprehensive Cryptographic API Misuse Detection: Fine-tuning Discriminative LLMs on Sliced Code Snippets.
.- DUFuzz: Define-Use Chain Guided Fuzzing for RESTful API Vulnerability Discovery.
.- PrivEscope: Systematic Detection of Privilege Escalation Paths in Database Management Systems.
.- Cross-ISA Heterogeneous Component Generation and Endogenous Security Enhancement via Code Segmented Compilation.
.- Web, Mobile and Supply Chain Security .
.- Beyond Isolated Phishing Emails: Discovering Hidden Campaign Relationships with MCDA.
.- Nephology: Characterizing the Security of Base Images across Cloud Providers.
.- HostCFI: Host-Side Control-Flow Integrity for Unmodified Guest Kernels in Cloud Environments.
.- Security Weaknesses and Privacy Leakage in Mini-apps: An Analysis Based on Structural, Behavioral, and Indicators.
.- Reliability Analysis for Multi-Cloud Auditing Systems.
.- Security Measurement and Systematization .
.- Unveiling the Sentinels: Assessing AI Performance in Cybersecurity Peer Review.
.- Towards Personalized Information Security Awareness: A User-, Riskand Context-Based Framework Enhanced by Artificial Intelligence.
.- Semantic Capabilities and Limitations of Detection Rule Languages: A Systematization of Knowledge.
.- An Empirical Measurement Study of Authentication Mechanisms in Cloud-Based Password Managers.
.- Malware and Binary Analysis .
.- Seeing Through Compression: Static Detection of Packed IoT Malware.
.- FRIME-TCN: A Feature-Adaptive RIME Optimization Framework for Efficient Network Intrusion Detection.
.- OP-UMKL: Ordinality-Preserving Unsupervised Multi-Kernel Learning for Provenance-Graph-based APT Detection.
.- GraceTI: A Graph Relation-Aware Contrastive Embedding Method for Threat Intelligence.
.- Lightweight IoT Malware Detection via Adaptive Federated Aggregation and Transformer Distillation for Network Traffic.
.- Rethinking Neural Decompilation: Candidate Selection as the Hidden Bottleneck.
.- BinCryptID: Semantic-Structural Identification of Cryptographic Functions in Stripped Binaries.
.- RL-ChainGuard: Reinforcement Learning-based Evidence Chain Selection for Explainable Malware Detection.
