Harnessing the Speed and Accuracy of Machine Learning to Advance Cybersecurity

arXiv:2302.12415v3 Announce Type: replace
Abstract: As cyber attacks continue to increase in frequency and sophistication, detecting malware has become a critical task for maintaining the security of computer systems. Traditional signature-based methods of malware detection have limitations in detecting complex and evolving threats. In recent years, machine learning (ML) has emerged as a promising solution to detect malware effectively. ML algorithms are capable of analyzing large datasets and identifying patterns that are difficult for humans to identify. This paper presents …

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