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Software transformations to improve malware detection
Authors:Mihai Christodorescu  Somesh Jha  Johannes Kinder  Stefan Katzenbeisser  Helmut Veith
Affiliation:1. University of Wisconsin, Madison, USA
2. Technische Universit?t München, Munich, Germany
Abstract:Malware is code designed for a malicious purpose, such as obtaining root privilege on a host. A malware detector identifies malware and thus prevents it from adversely affecting a host. In order to evade detection, malware writers use various obfuscation techniques to transform their malware. There is strong evidence that commercial malware detectors are susceptible to these evasion tactics. In this paper, we describe the design and implementation of a malware transformer that reverses the obfuscations performed by a malware writer. Our experimental evaluation demonstrates that this malware transformer can drastically improve the detection rates of commercial malware detectors.
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