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Detecting Java Class Theft using Static API Trace Birthmark  

Park, Hee-Wan (KAIST 전산학)
Choi, Seok-Woo (KAIST 전산학)
Lim, Hyun-Il (KAIST 전산학)
Han, Tai-Sook (KAIST 전산학)
Publication Information
Journal of KIISE:Computing Practices and Letters / v.14, no.9, 2008 , pp. 911-915 More about this Journal
Abstract
Software birthmark is the inherent characteristics that can identify a program. In this paper, we propose a Java class theft detection technique based on static API traces of class files. We utilize control flow analysis to increase resilience, and we apply the semi-global alignment trace comparison algorithm to increase credibility. The credibility and resilience experiments for XML parsers show that our birthmark is more efficient than existing birthmarks.
Keywords
Code Theft; Static Analysis; Software Birthmark;
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