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学术报告:Towards Obfuscation-Resilient Software Plagiarism Detection
文章来源: 发布时间:2015-07-27 【字号:

题目:Towards Obfuscation-Resilient Software Plagiarism Detection

报告人:Dinghao Wu教授

时间:2015730日(星期四), 下午13:30

地点:中国科学院信息工程研究所3号楼3224

Abstract:

Software plagiarism, an act of illegally copying others’ code, has become a serious concern for honest software companies and the open source community. In this talk, I will present two program logic and semantics based methods that are obfuscation resilient. The first method is based on program behavior deviation detection. By detecting deviations between two programs, we rule out non-plagiarism; otherwise, by a repeated probabilistic argument, we conclude it is a plagiarism case. The second method uses a novel concept called longest common subsequences (LCS) of semantically equivalent basic blocks. We first compute the semantic equivalence of basic blocks, and then detect the LCS of two paths from two programs under consideration with the same input, with binary basic blocks as the sequence elements.  A similarity score is calculated based on the relative LCS length, which indicates the behavior similarity of the two programs under consideration.  The results of these two methods are published in ISSRE’14 and FSE’14.

Bio:

Dinghao Wu is an Assistant Professor in the College of Information Sciences and Technology at The Pennsylvania State University. He received his Ph.D. in Computer Science from Princeton University in 2005. He was a research engineer at Microsoft in the Center for Software Excellence and the Windows Azure Division before joined Penn State. Dinghao does research on software systems, including software security, software protection, software analysis and verification, information and software assurance, software engineering, and programming languages. He has worked on foundational proof-carrying code, typed assembly languages, program analysis, and software and systems security projects. His current projects include lock-free concurrent security monitoring, real-time concurrent information flow tracking, and semantics-based software plagiarism detection. He also leads a project on cloud computing for energy and environmental sustainability. His research has been funded by National Science Foundation (NSF), Office of Naval Research (ONR), and U.S. Department of Energy (DOE).

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