Collaborative Support Vector Machine for Malware Detection

Abstract

Malware has been the primary threat to computer and network for years. Traditionally, supervised learning methods are applied to detect malware. But supervised learning models need a great number of labeled samples to train models beforehand, and it is impractical to label enough malicious code manually. Insufficient training samples yields imperfect… (More)
DOI: 10.1016/j.procs.2017.05.063

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