FINISH: Efficient and Scalable NMF-Based Federated Learning for Detecting Malware Activities
Author:
Affiliation:
1. Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan
2. National Institute of Information and Communications Technology, Koganei, Japan
3. University of Hyogo, Kobe, Hyogo, Japan
Funder
Ministry of Science and Technology, Taiwan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Human-Computer Interaction,Information Systems,Computer Science (miscellaneous)
Link
http://xplorestaging.ieee.org/ielx7/6245516/10349221/10179267.pdf?arnumber=10179267
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1. Scanning the Scanners
2. An Incident Analysis System NICTER and Its Analysis Engines Based on Data Mining Techniques
3. A Proposal of Metrics for Botnet Detection Based on Its Cooperative Behavior
4. Automated Detection of Malware Activities Using Nonnegative Matrix Factorization
5. A multilevel approach for nonnegative matrix factorization
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