Machine Learning for Cyber Security: 5th International Conference, ML4CS 2023, Yanuca Island, Fiji, December...

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Dan Dongseong Kim Chao Chen

Machine Learning for Cyber Security

5th International Conference, ML4CS 2023, Yanuca Island, Fiji, December 4–6, 2023, Proceedings...

Dan Dongseong Kim, Chao Chen

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English

Springer Nature
23 April 2024

Computer security; Network security; Machine learning

Series: Lecture Notes in Computer Science

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.

Edited by: Dan Dongseong Kim, Chao Chen
Imprint: Springer Nature
Country of Publication: Singapore
Volume: 14541
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9789819724574
ISBN 10: 9819724570
Series: Lecture Notes in Computer Science
Pages: 174
Publication Date: 23 April 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

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.