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Machine Learning for Cyber Security : 5th International Conference, ML4CS 2023, Yanuca Island, Fiji, December 4–6, 2023, Proceedings / edited by Dan Dongseong Kim, Chao Chen.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

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Format:
Book
Contributor:
Kim, Dan Dongseong, editor.
Chen, Chao, editor.
Series:
Lecture Notes in Computer Science, 1611-3349 ; 14541
Language:
English
Subjects (All):
Data protection.
Computer engineering.
Computer networks.
Computer networks--Security measures.
Data and Information Security.
Computer Engineering and Networks.
Mobile and Network Security.
Local Subjects:
Data and Information Security.
Computer Engineering and Networks.
Mobile and Network Security.
Physical Description:
1 online resource (186 pages)
Edition:
1st ed. 2024.
Place of Publication:
Singapore : Springer Nature Singapore : Imprint: Springer, 2024.
Summary:
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.
Contents:
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.
ISBN:
981-9724-58-9

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