Title
A Graph Approach to Quantitative Analysis of Control-Flow Obfuscating Transformations
Abstract
Modern obfuscation techniques are intended to discourage reverse engineering and malicious tampering of software programs. We study control-flow obfuscation, which works by modifying the control flow of the program to be obfuscated, and observe that it is difficult to evaluate the robustness of these obfuscation techniques. In this paper, we present a framework for quantitative analysis of control-flow obfuscating transformations. Our framework is based upon the control-flow graph of the program, and we show that many existing control-flow obfuscation techniques can be expressed as a sequence of basic transformations on these graphs. We also propose a new measure of the difficulty of reversing these obfuscated programs, and we show that our framework can be used to easily evaluate the space penalty due to the transformations.
Year
DOI
Venue
2009
10.1109/TIFS.2008.2011077
IEEE Transactions on Information Forensics and Security
Keywords
Field
DocType
control-flow obfuscation,software protection,modern obfuscation technique,software program,software metrics,control flow,obfuscation technique,control-flow graph,reverse engineering,software programs,computer prime,control-flow obfuscating transformation,existing control-flow obfuscation technique,quantitative analysis,control-flow obfuscating transformations,basic transformation,code obfuscation,graph approach,obfuscated program,malicious tampering,security of data,intellectual property,logic,helium,robust control,control engineering,application software,control flow graph,software metric,cryptography
Control flow graph,Computer science,Reverse engineering,Control flow,Theoretical computer science,Robustness (computer science),Obfuscation (software),Software metric,Application software,Obfuscation
Journal
Volume
Issue
ISSN
4
2
1556-6013
Citations 
PageRank 
References 
10
0.56
13
Authors
3
Name
Order
Citations
PageRank
Hsin-Yi Tsai1955.87
Yu-Lun Huang238226.06
David Wagner312563933.74