Security and Privacy in Communication Networks

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

Häftad, Engelska, 2026

Del 688 i serien Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

1 139 kr

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Beskrivning

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

Utgivningsdatum:2026-06-04
Mått:155 x 235 x 34 mm
Vikt:925 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Antal sidor:605
Förlag:Springer Nature Switzerland AG
ISBN:9783032234490

Utforska kategorier

Referensverk och tvärvetenskap inom Samhälle och politik
IT-säkerhet inom Data och IT
Nätverk och kommunikation inom Data och IT

Innehållsförteckning

.- 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.

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Security and Privacy in Communication Networks

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

AvWei Liang,Sun-Yuan Kung

Häftad, Engelska, 2026

Del 688 i serien Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

1 139 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

Produktinformation

Utgivningsdatum:2026-06-04
Mått:155 x 235 x 34 mm
Vikt:925 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Antal sidor:605
Förlag:Springer Nature Switzerland AG
ISBN:9783032234490

Utforska kategorier

Referensverk och tvärvetenskap inom Samhälle och politik
IT-säkerhet inom Data och IT
Nätverk och kommunikation inom Data och IT

Innehållsförteckning

.- 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.