Del 0 - Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

Security and Privacy in Communication Networks

Nyhet

21st EAI International Conference, SecureComm 2025, Xiangtan, China, July 4–6, 2025, Proceedings, Part II

Häftad, Engelska, 2026

AvWei Liang,Sun-Yuan Kung,Meikang Qiu

1 779 kr

Kommande

This four-volume set LNISCT 687-690 constitutes the proceedings of the 21st EAI International Conference on Security and Privacy in Communication Networks, SecureComm 2025, held in Xiangtan, China, during July 4 - 6, 2025.The 119 full papers included in these volumes were carefully reviewed and selected from 341 submissions. They are organized in the following topical sections:Part I: Distributed and Network Security; ML/AI Security.Part II: ML/AI Security; CyberSecurity.Part III: CyberSecurity; Cryptography and Authentication.Part IV: Cryptography and Authentication; Security and Optimization.

Produktinformation

Utgivningsdatum2026-05-23
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
FörlagSpringer Nature Switzerland AG
ISBN9783032234490

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.- ML/AI Security..- SVD-Based Efficient Communication Scheme for Heterogeneous Federated Learning..- IncreTTP: An Incremental TTPs Classification Model..- Login, Logout, Reset: Measuring Security and Privacy Issues in Real-World Web Logins..- Location Privacy Protection for VANETs based on Dynamically Adjustable Security Coefficient..- BPGT: A Novel Privacy-Preserving K-Means Clustering Framework to Guarantee Local $d_{\chi}$-privacy..- Hamk-CFI: A Hardware-assisted Kernel Control Flow Protection Framework For Cloud Environments..- PEARL: A Reinforcement Learning-Based Attack Analysis Approach for Security and Robustness Assessment of Smart Home Systems..- The RPKI and Its Hidden Guardians: An Empirical Analysis of Their Relationship and Security Implications..- FedCC: Robust Federated Learning against Model Poisoning Attacks..- FedCLF: Contrastive Learning-driven Framework for Mitigating Data Heterogeneity in Federated Learning..- FedSND:Federated Learning with Symmetric Noise Decentralized Orthogonal Encryption..- Group-Based Parallel Split Federated Learning..- A Verifiable Federated Learning Aggregation Scheme Based on Homomorphic Hashing..- A Lightweight Image Steganography Scheme Based on Invertible Neural Network Architecture with Progressive Channel Attention..- Defending Against Malicious Clients in Robust Heterogeneous Federated Learning..- CyberSecurity..- A Few-Shot-Based Model-Agnostic Meta-Learning for Intrusion Detection in Secure of In-vehicle Network..- A Robustness Optimization Mechanism for Intrusion Detection Models Based on Dynamic Ensemble Learning..- BFDet: A Method for Detecting Malicious Traffic with Ultra-Low False Positive Rate Based on TLS Behavior Flow..- DARD: Dice Adversarial Robustness Distillation Against Adversarial Attacks..- EvasionEval: A Benchmark for LLMs in Evaluating Advanced Defense Evasion Techniques..- Flow Dissector: A Flow Slicing Representation with a Pre-trained Model for Varied Malicious Traffic Classification..- From Dark Network to Honeypot: Analysis and Traceability of Multi-prefix IPv6 Network Attacks..- Insights into Ransomware Detection based on Semantic Understanding..- Log Anomaly Detection based on Time-Delta Sequential Feature..- Log Semantic Parsing based on Sequence Annotation in Security Operations..- MOT-Fuzz: A Novel Directed Greybox Fuzzing with Multiple Ordered Target Basic Blocks for Multistep Vulnerabilities..- MFRWF: Enhance Website Fingerprinting Robustness Against website content updates and background noise traffic..- One Trace is Possible: A Method for Small-Sample Profiling Side-Channel Analysis in Communication Environments..- Task-Driven GAN for Class-Imbalanced Intrusion Detection..- Two Birds with One Stone: Multi-Task Detection and Attribution of LLM-Generated Text.