Emerging Information Security and Applications

5th International Conference, EISA 2024, Changzhou, China, October 18-19, 2024, Proceedings
Herausgegeben:Li, Wenjuan; Chen, Liqun; Lopez, Javier

• Broschiertes Buch

Produktbeschreibung

This book constitutes the refereed proceedings of the 5th International Conference on EISA--Emerging Information Security and Applications, EISA 2024, held in Changzhou, China, during October 18-19, 2024.

The 15 full papers and 3 short papers included in this book were carefully reviewed and selected from 52 submissions. The topics covered adversarial techniques, intrusions that may threaten the security of various assets, including information and applications, have become more complex.

Produktdetails

• Communications in Computer and Information Science 2266
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-80418-2
• Seitenzahl: 268
• Erscheinungstermin: 18. Januar 2025
• Englisch
• Abmessung: 235mm x 155mm x 15mm
• Gewicht: 412g
• ISBN-13: 9783031804182
• ISBN-10: 303180418X
• Artikelnr.: 72045839

Inhaltsangabe

.- High-Efficiency Phase-Index Correlation Delay Shift Keying Modulation.
.- Federated Learning Poison Attack Detection Scheme Based on Gradient Similarity.
.- A Privacy-Preserving and Fault-Tolerant Data Aggregation Scheme in Smart Grids.
.- Local Differential Privacy for Key-Value Data Collection and Analysis Based on Privacy Preference and Adaptive Sampling.
.- Comparative Study of Machine Learning Approaches for Phishing Website Detection.
.- Exploring Interpretability in Backdoor Attacks on Image.
.- Attribute-Based Secret Key Signature Scheme.
.- Digital token transaction tracing method.
.- GPT-based WebAssembly Instruction Analysis for Program Language Processing.
.- Research on Key Technologies of Fair Deep Learning.
.- Adaptive Differential Privacy Based Optimization Scheme for Federated Learning.
.- Cascading failures model with noise interference in supply chain networks.
.- DefMPA: Defending Model Poisoning Attacks in Federated Learning via Model Update Prediction.
.- SDDRM: An Optimization Algorithm for Localized Differential Privacy Based on Data Sensitivity Differences.
.- Blockchain-based key management scheme in Internet of Things.
.- Privacy Optimization of Deep Recommendation Algorithm in Federated Framework.
.- Delegated Proof of Stake Consensus Mechanism Based on the Overall Perspective of Voting.
.- A Distributed Privacy-preserving Data Aggregation Scheme for MaaS Data Sharing.