Title
DepSim: a dependency-based malware similarity comparison system
Abstract
It is important for malware analysis that comparing unknown files to previously-known malicious samples to quickly characterize the type of behavior and generate signatures. Malware writers often use obfuscation, such as packing, junk-insertion and other means of techniques to thwart traditional similarity comparison methods. In this paper, we introduce DepSim, a novel technique for finding dependency similarities between malicious binary programs. DepSim constructs dependency graphs of control flow and data flow of the program by taint analysis, and then conducts similarity analysis using a new graph isomorphism technique. In order to promote the accuracy and antiinterference capability, we reduce redundant loops and remove junk actions at the dependency graph pre-processing phase, which can also greatly improve the performance of our comparison algorithm. We implemented a prototype of DepSim and evaluated it to malware in the wild. Our prototype system successfully identified some semantic similarities between malware and revealed their inner similarity in program logic and behavior. The results demonstrate that our technique is accurate.
Year
DOI
Venue
2010
10.1007/978-3-642-21518-6_35
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Keywords
Field
DocType
semantic similarity,novel technique,inner similarity,similarity analysis,new graph isomorphism technique,malware analysis,dependency-based malware similarity comparison,taint analysis,dependency similarity,dependency graph,depsim constructs dependency graph
Data mining,Graph isomorphism,Computer security,Computer science,Network security,Theoretical computer science,Taint checking,Obfuscation,Malware,Dependency graph,Data flow diagram,Malware analysis
Conference
Volume
Issue
ISSN
6584 LNCS
null
16113349
Citations 
PageRank 
References 
0
0.34
14
Authors
5
Name
Order
Citations
PageRank
Yang Yi100.68
Lingyun Ying2243.41
Wang Rui300.34
Purui Su49413.71
Deng-Guo Feng51991190.95