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The proliferation of malware variants poses a significant challenges to traditional malware detection approaches, such as signature-based methods, necessitating the development of advanced machine learning techniques. In this research, we present a n
Externí odkaz:
http://arxiv.org/abs/2412.18932
Many different machine learning and deep learning techniques have been successfully employed for malware detection and classification. Examples of popular learning techniques in the malware domain include Hidden Markov Models (HMM), Random Forests (R
Externí odkaz:
http://arxiv.org/abs/2307.11032
Publikováno v:
Journal of Computer Virology and Hacking Techniques; March 2024, Vol. 20 Issue: 1 p173-184, 12p
This book constitutes the refereed proceedings of the Fourth International Conference on Futuristic Trends in Network and Communication Technologies, FTNCT 2021. The prime aim of the conference is to invite researchers from different domains of netwo