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CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks

CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks

Iqbal H. Sarker
    AAML
ArXiv (abs)PDFHTML

Papers citing "CyberLearning: Effectiveness Analysis of Machine Learning Security Modeling to Detect Cyber-Anomalies and Multi-Attacks"

4 / 4 papers shown
Title
Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation
Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation
Mirza Akhi Khatun
S. Memon
Ciarán Eising
L. L. Dhirani
55
25
0
17 Jan 2024
Data-Driven Intelligence can Revolutionize Today's Cybersecurity World: A Position Paper
Data-Driven Intelligence can Revolutionize Today's Cybersecurity World: A Position Paper
Iqbal H. Sarker
Helge Janicke
Leandros A. Maglaras
S. Çamtepe
21
2
0
09 Aug 2023
Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection
Decentralized Online Federated G-Network Learning for Lightweight Intrusion Detection
Mert Nakıp
Baran Can Gül
Erol Gelenbe
93
8
0
22 Jun 2023
Machine and Deep Learning for IoT Security and Privacy: Applications, Challenges, and Future Directions
Machine and Deep Learning for IoT Security and Privacy: Applications, Challenges, and Future Directions
Subrato Bharati
Prajoy Podder
88
39
0
24 Oct 2022