Machine Learning for Cyber Security (eBook, PDF)

5th International Conference, ML4CS 2023, Yanuca Island, Fiji, December 4-6, 2023, Proceedings
Redaktion: Kim, Dan Dongseong; Chen, Chao

• Format: PDF

Produktbeschreibung

This book constitutes the referred proceedings of the 5th International Conference on Machine Learning for Cyber Security, ML4CS 2023, held in Yanuca Island, Fiji, during December 4-6, 2023.

The 11 full papers presented in this book were carefully reviewed and selected from 35 submissions. They cover a variety of topics, including cybersecurity, AI security, machine learning security, encryption, authentication, data security and privacy, cybersecurity forensic analysis, vulnerability analysis, malware analysis, anomaly and intrusion detection.

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 174
• Erscheinungstermin: 22. April 2024
• Englisch
• ISBN-13: 9789819724581
• Artikelnr.: 70574597

Inhaltsangabe

Keystroke Transcription from Acoustic Emanations Using Continuous Wavelet Transform.- Strengthening Cyber Security Education Designing Robust Assessments for Chat GPT Generated Answers.- Pass File Graphical Password Authentication based on File Browsing Records.- On the Role of Similarity in Detecting Masquerading Files.- A Password-based Mutual Authenticated Key Exchange Scheme by Blockchain for WBAN.- Traffic Signal Timing Optimization Based on Intersection Importance in Vehicle Road Collaboration.- A client side watermarking with private class in Federated learning.- Research on Evasion and Detection of Malicious JavaScript Code.- Tackling Non IID for Federated Learning with Components Alignment.- Security on top of Security Detecting Malicious Firewall Policy Changes via K Means Clustering.- Penetrating Machine Learning Servers via Exploiting BMC Vulnerability.