BinClone: Detecting Code Clones in Malware

Abstract

To gain an in-depth understanding of the behaviour of a malware, reverse engineers have to disassemble the malware, analyze the resulting assembly code, and then archive the commented assembly code in a malware repository for future reference. In this paper, we have developed an assembly code clone detection system called BinClone to identify the code clone fragments from a collection of malware binaries with the following major contributions. First, we introduce two deterministic clone detection methods with the goals of improving the recall rate and facilitating malware analysis. Second, our methods allow malware analysts to discover both exact and inexact clones at different token normalization levels. Third, we evaluate our proposed clone detection methods on real-life malware binaries. To the best of our knowledge, this is the first work that studies the problem of assembly code clone detection for malware analysis.