Paper Info
Title
Function matching-based binary-level software similarity calculation
Abstract
This paper proposes a method to calculate similarities of software without any source code information. The proposed method can be used for various applications such as detecting the source code theft and copyright infringement, as well as locating updated parts of software including malware. To determine the similarities of software, we used an approach that matches similar functions included in software. Our function-based matching process is composed of two steps. In step 1, the structural information of call graph in binary file is used to match functions, and the matched functions are not processed in step 2 to reduce the number of detailed matching. In step 2, by using instruction mnemonics, N-gram similarity-based matching is performed. Using the structural matching proposed in this paper, about 30% improvement in the matching performance is achieved with the four-tuple matching which also reduces the false positive rate compared to previous studies. Our other experimental results showed that, in comparison to source code-based approaches, our proposed method has only about 3% difference in similarity calculation with real software samples. Therefore, we argue that our proposed method makes a contribution in the field of binary-based software similarity calculation.
Year
DOI
Venue
2013
10.1145/2513228.2513300
RACS
Keywords
Field
DocType
matching performance,four-tuple matching,source code information,function-based matching process,n-gram similarity-based matching,real software sample,detailed matching,binary-based software similarity calculation,binary-level software similarity calculation,structural matching,malware,n gram,call graph,static analysis
Data mining,False positive rate,Computer science,Source code,Static analysis,Call graph,Software,Artificial intelligence,n-gram,Binary number,Computer vision,Algorithm,Malware
Conference
Citations 
PageRank 
References 
5
0.47
7
Authors
3
Name
Order
Citations
PageRank
Yeo Reum Lee161.16
BooJoong Kang211811.55
Eul Gyu Im317524.80