Malware Detection Using Perceptrons and Support Vector Machines

  • Gavrilut D
  • Cimpoesu M
  • Anton D
 et al. 
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Abstract

In this paper we explore the capabilities of a framework that can use
different machine learning algorithms to successfully detect malware
files, aiming to minimize the number of false positives. We report the
results obtained in our framework, working firstly with cascades of
one-sided perceptron and kernelized one-sides perceptrons and secondly
with cascade of one-sided support vector machines.

Author-supplied keywords

  • Malware detection; perceptrons; Support Vector Mac

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Authors

  • Dragos Gavrilut

  • Mihai Cimpoesu

  • Dan Anton

  • Liviu Ciortuz

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