Publication Date

Spring 5-15-2015

Degree Type

Master's Project

Degree Name

Master of Science (MS)

Department

Computer Science

First Advisor

Mark Stamp

Second Advisor

Thomas Austin

Third Advisor

Sami Khuri

Abstract

Well-designed malware can evade static detection techniques, such as signature scanning. Dynamic analysis strips away one layer of obfuscation and hence such an approach can potentially provide more accurate detection results. However, dynamic analysis is generally more costly than static analysis. In this research, we analyze the effectiveness of using dynamic analysis to enhance the training phase, while using only static techniques in the detection phase. Relative to a fully static approach, the additional overhead is minimal, since training is essentially one-time work.

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