ANALYSIS OF MACHINE LEARNING METHODS ON MALWARE DETECTION

Aydogan E., Sen S.

22nd IEEE Signal Processing and Communications Applications Conference (SIU), Trabzon, Turkey, 23 - 25 April 2014, pp.2066-2069 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2014.6830667
  • City: Trabzon
  • Country: Turkey
  • Page Numbers: pp.2066-2069
  • Keywords: malware analysis and detection, machine learning
  • Akdeniz University Affiliated: No

Abstract

Nowadays, one of the most important security threats are new, unseen malicious executables. Current anti-virus systems have been fairly successful against known malicious softwares whose signatures are known. However they are very ineffective against new, unseen malicious softwares. In this paper, we aim to detect new, unseen malicious executables using machine learning techniques. We extract distinguishing structural features of softwares and, employ machine learning techniques in order to detect malicious executables.