Security and Privacy in Communication Networks : 20th EAI International Conference, SecureComm 2024, Dubai, United Arab Emirates, October 28-30, 2024, Proceedings, Part IV (Lecture Notes of the Institute for Computer Sciences, Social Informatics and

Security and Privacy in Communication Networks : 20th EAI International Conference, SecureComm 2024, Dubai, United Arab Emirates, October 28-30, 2024, Proceedings, Part IV (Lecture Notes of the Institute for Computer Sciences, Social Informatics and

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 397 p.
  • 言語 ENG
  • 商品コード 9783031944574
  • DDC分類 005.8

Full Description

This four-volume set LNISCT 627-630 constitutes the proceedings of the 20th EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2024, held in Dubai, United Arab Emirates during October 28 - 30, 2024.

The 81 full papers were carefully reviewed and selected from 225 submissions. The proceedings focus on

Privacy and Cryptography

AI for cybersecurity and Adversial models

Quantum Computing in Cybersecurity

Network Security

Blockchain and Cryptocurrencies

Fuzzing and IoT security

Malware and Attack Analysis

Web Security

Authentication

Large Language Model for Cybersecurity

Security Assessments

Contents

Authentication.- Pulse to-Pair: Heartbeat based Authentication of IoT Devices for Elderly Care.- A Lightweight Group Authentication Framework for Cross Domain Internet of Things.- DPU LARD: DPU Leveraged Attestation of Remote Devices for Security of OT Networks.- Gait4Auth: Enhancing Identification and Security in Gait Based Authentication.- A Hardware Oriented Lightweight Block Cipher and Its Application in Surveillance Video.- TGSA: Trajectory Group Semantic Anonymization.- Large Language Model for Cybersecurity.- Can't say cant? Measuring and Reasoning of Dark Jargons in Large Language Models.- Cybersecurity with LLMs and RAGs: Challenges and Innovations.- Enhancing Pre Trained Language Models for Vulnerability Detection via Semantic Preserving Data Augmentation.- K-BOOST: A Cyber Security NER Model with Knowledge Augmentation via BERT.- FLKT: Improving the Fidelity and Robustness of Federated Learning Aggregation Rules via the Key data and Trap model.- Poisoning Attack on Federated Learning with Non IID Data: A Historical-Global-Model-Based Approach.- Security Assessments.- A Comprehensive Evaluation of the Impact on Tor Network Anonymity Caused by ShadowBridge.- ADG-Dedup: Adaptive Dynamic Grained Deduplication Scheme for IoT Data in Cloud Storage.- Enhancing Reliability in Open Rating Systems: A Trust Aware Filtering Approach.- Graph Injection Attack based on Node Similarity and Non linear Feature Injection Strategy.- Assessing and Prioritizing Ransomware Risk Based on
Historical Victim Data.- Solving ILWE Problem More Efficiently and Application to BLISS Side Channel Attack.

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