SHF: Small: Towards Obfuscation-Resilient Software Plagiarism Detection

软件剽窃是一种违反原始许可条款，将他人的全部或部分代码重新使用到自己的程序中的行为。随着软件产业的快速发展和开源项目的涌现，软件剽窃已经成为知识产权保护和开源软件产业“健康”的严重威胁。与此同时，软件剽窃（即所谓的应用程序重新包装）已经成为手机应用市场上一种更为普遍的现象，通过在原始应用中插入恶意载荷来获取金钱利润或传播恶意软件。为了解决这一威胁，计算机辅助的自动抄袭检测工具应该发挥主要作用。然而，现有的抄袭检测方案对代码混淆没有弹性，而且通常可以被（在大多数情况下相当简单的）基于代码混淆的反检测工具击败，这些工具是免费提供的。本课题对软件剽窃检测问题进行了系统的研究。提出的PC应用程序剽窃检测方法利用程序逻辑和最长语义等效基本块子序列。它们不仅能够检测出部分程序抄袭，而且还提供了对混淆弹性的正式保证。提出的移动应用程序方法利用用户界面进行抄袭检测，这种独特的设计角度使其能够击败各种代码混淆技术。我们提出的研究将显著阻止软件剽窃的意图或实践。它不仅可以成为知识产权诉讼中收集强有力的剽窃证据的有用工具，而且还可以为开源社区和移动应用市场创造一个更加健康和值得信赖的共享环境。教育和传播倡议也将产生更广泛的影响。

Software plagiarism is an act of reusing someone else's code, in whole or in part, into one own program in a way violating the terms of original license. Along with the rapid developing software industry and the burst of open source projects, software plagiarism has become a very serious threat to Intellectual Property Protection and the "healthiness" of the open-source-embracing software industry. Meanwhile, software plagiarism (and what is called app repackaging) has become an even more common phenomenon in the mobile app markets for monetary profit or propagation of malware by inserting malicious payloads into the original apps. To address this threat, computer-aided, automated plagiarism detection tools should play a major role. However, existing plagiarism detection schemes are not resilient to code obfuscation, and often they can be defeated by (in most cases rather simple) code-obfuscation-based counter-detection tools which are freely available.In this project, the software plagiarism detection problem is studied in a systematic way. The proposed plagiarism detection methods for PC applications leverage program logic and longest semantically-equivalent-basic-block subsequences. They are capable of detecting partial program plagiarism and also provide formal guarantee on obfuscation resilience. The proposed method for mobile apps exploits user interface for plagiarism detection, and this unique design angle empowers it to defeat various code obfuscation techniques. Our proposed research will significantly deter the intention or practice of software plagiarism. It will not only serve as a useful tool in collecting strong plagiarism evidences for lawsuits related to intellectual property, but also promote a more healthy and trustworthy sharing environment for the open source community and for the mobile app markets. Broader impact will also result from the education and dissemination initiatives.