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Security and Privacy in Communication Networks 21st EAI International Conference, SecureComm 2025, Xiangtan, China, July 4–6, 2025, Proceedings, Part I

Aus der Reihe Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Beschreibung

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...

Beschreibung

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.

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

24.04.2026
Abbildungen

XIII, 630 p. 163 illus., 149 illus. in color.
Herausgeber Wei Liang + weitere

Produktdetails

Einband

Taschenbuch
Erscheinungsdatum

24.04.2026
Abbildungen

XIII, 630 p. 163 illus., 149 illus. in color.
Herausgeber
Verlag Springer
Seitenzahl

630
Maße (L/B/H)

23,5/15,5/3,5 cm
Gewicht

961 g
Sprache

Englisch
ISBN

978-3-032-23446-9
Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Security and Privacy in Communication Networks

  • .- Distributed and Network Security.

    .- A Fault-Tolerant Block Allocation Scheme for Collaborative Storage Blockchain Systems.

    .- A Double-Layer Blockchain-Assisted Anonymous Cross-Domain Authentication and Transaction Scheme for Metaverse.

    .- Adaptive On-Chain and Off-Chain Communication Management Based on SDN and Blockchain.

    .- BDSV: A Blockchain-based Reliable and Efficient Batch Digital Signature Verification Scheme for IoV.

    .- BFT-MS: Asynchronous BFT Protocol Using Bounded Memory.

    .- Fair Exchange of Trained Machine Learning Models Based on Permissioned Blockchain and Zero-Knowledge Contingent Payment.

    .- SaFeBridge: Consensus-Agnostic Asset Transfer with Slow-Approval Fast-Exit Principles.

    .- Security Detection Method for Wireless Sensor Networks Based on Self-Supervised Learning and Deep Learning.

    .- Securing Snapshot Pruning in IOTA Tangle 2.0: A Cooperative Deep Reinforcement Learning Approach for Edge-Cloud Smart Meter Networks.

    .- TACA: Blockchain-Based Traceable and Anonymous Cross-Domain Authentication Scheme for IIoT.

    .- Spatiotemporal Cross-Domain Integrated Insights: Mitigating Fraudulent Activities on Ethereum.

    .- PIRchain: Blockchain-Enhanced Privacy-Preserving Inter-domain Routing.

    .- Consortium Blockchain-Based Anti-Plagiarism Scheme for Multi-NFT Marketplaces.

    .- Cryptocurrency Transaction Anomaly Detection Based on Semi-Supervised Learning and Graph Neural Network.

    .- Hardware-assisted Secure Decentralized Cloud Storage via Self-audit and Self-repair.

    .- RdBFT: Faster Asynchronous BFT Protocol through Random Binary Agreement.

    .- Antitoxin: A Framework for Controlling Persistent Backdoors in Federated Learning.

    .- MDC-Net:Multi-Dimensional Cross-Domain Collaborative Network for Image Manipulation Localization.

    .- The Framework Of Variational Mode Decomposition Based For DDoS Detection.

    .- DCAPSCR: A Decentralized Conditional Anonymous Payment System With Collaborative Regulation.

    .- SCFA: Stacked Classifier with Feature Augmentation for Imbalanced Node Classification in Intelligent Internet-of Things.

    .- ML/AI Security.

    .- FL(DP)2 : Federated Learning with Dynamic Personalized Differential Privacy.

    .- FLARE: Feature-based Lightweight Aggregation for Robust Evaluation of IoT Intrusion Detection.

    .- Knowledge Distillation for Federated Learning with Many Noisy Clients.

    .- Low Energy Consumption Hierarchical Federated Learning.

    .- LPFL-RL: A Lightweight Privacy-Preserving Federated Learning Scheme with Robustness Against Low-Quality Users in Cloud-Edge Collaborative Environments.

    .- Heterogeneity-aware semi-asynchronous federated learning.

    .- pFedDDS: Personalized Federated Learning via Dual defense Strategies.

    .- PPCM-Fed: Privacy-Preserving Cross-Modal Federated Learning in IoT.

    .- Security-Aware and Energy-Efficient Federated Learning in LEO Satellite Edge Micro-clouds: A Noise-Adaptive Allocation Framework.