Security and Privacy in Social Networks and Big Data

11th International Symposium, SocialSec 2025, Wuhan, China, December 5–7, 2025, Proceedings

AvLiming Zhai,Qing Guo

Häftad, Engelska, 2026

Del 16327 i serien Lecture Notes in Computer Science

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Beskrivning

This book LNCS 16327 constitutes the referred proceedings of the 11th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2025, held in Wuhan, China during December 5–7, 2025.The 12 full papers presented in this volume were carefully reviewed and selected from 25 submissions.The SocialSec conference series aims to provide a leading-edge forum to foster interactions among researchers and developers within the security and privacy communities in social networks and big data.

Produktinformation

Utgivningsdatum:2026-02-26
Mått:155 x 235 x 13 mm
Vikt:365 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:225
Förlag:Springer Verlag, Singapore
ISBN:9789819570263

Utforska kategorier

IT-säkerhet inom Data och IT
Nätverk och kommunikation inom Data och IT
Tillämpad datateknik inom Data och IT

Innehållsförteckning

.- PMDID: A Privacy-Preserving and Migratable Decentralized Identity Using PUF and Blockchain..- Lightweight Mutual Authentication for End-to-End Communication in Satellite Internet..- Parallel Implementation of Activation Functions and Arithmetic Operations Based on TFHE..- Enabling Secure and Efficient Authenticated Edge Inference for the Internet of Things..- New insights into effects of fluctuations on dynamical degradation of digital chaos..- Game-Theoretic Defense Against Encrypted Data Poisoning in Federated Learning for Social Networks..- Physical Layer Security via Movable Antenna in Near-Field..- A Privacy-Preserving Data Aggregation Scheme with Inner-Product Encryption for Smart Grids..- A Privacy-Preserving Cross-Chain Access Control Scheme Based onThreshold Fully Homomorphic Encryption..- FG-LAS: A Fault-Tolerant and Group Handover LightweightAuthentication Scheme for Dynamic and Heterogeneous STINEnvironments..- Wavelet Residue Contrastive Learning for Deep Steganalysis..- APrivacy-PreservingSemi-SupervisedAlgorithmforNon-Gaussian NoiseEnvironments.