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Binary code clone analysis is an important technique which has a wide rangeof applications in software engineering (e.g., plagiarism detection, bugdetection). The main challenge of the topic lies in the semantics-equivalentcode transformation (e.g., optimization, obfuscation) which would alterrepresentations of binary code tremendously. Another chal- lenge is thetrade-off between detection accuracy and coverage. Unfortunately, existingtechniques still rely on semantics-less code features which are susceptible tothe code transformation. Besides, they adopt merely either a static or adynamic approach to detect binary code clones, which cannot achieve highaccuracy and coverage simultaneously. In this paper, we propose asemantics-based hybrid approach to detect binary clone functions. We execute atemplate binary function with its test cases, and emulate the execution ofevery target function for clone comparison with the runtime informationmigrated from that template function. The semantic signatures are extractedduring the execution of the template function and emulation of the targetfunction. Lastly, a similarity score is calculated from their signatures tomeasure their likeness. We implement the approach in a prototype systemdesignated as BinMatch which analyzes IA-32 binary code on the Linux platform.We evaluate BinMatch with eight real-world projects compiled with differentcompilation configurations and commonly-used obfuscation methods, totallyperforming over 100 million pairs of function comparison. The experimentalresults show that BinMatch is robust to the semantics-equivalent codetransformation. Besides, it not only covers all target functions for cloneanalysis, but also improves the detection accuracy comparing to thestate-of-the-art solutions.

BinMatch: A Semantics-based Hybrid Approach on Binary Code Clone Analysis