Aug. 17, 2022, 1:20 a.m. | Aqib Rashid, Jose Such

cs.CR updates on arXiv.org arxiv.org

Over the years, most research towards defenses against adversarial attacks on
machine learning models has been in the image recognition domain. The malware
detection domain has received less attention despite its importance. Moreover,
most work exploring these defenses has focused on several methods but with no
strategy when applying them. In this paper, we introduce StratDef, which is a
strategic defense system tailored for the malware detection domain based on a
moving target defense approach. We overcome challenges related to …

adversarial attacks defense detection lg malware malware detection

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