Source Analysis Research
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Stylistic analysis can de-anonymize code, even compiled code
A presentation today at Defcon from Drexel computer science prof Rachel Greenstadt and GWU computer sicence prof Aylin Caliskan builds on the pair's earlier work in identifying the authors of software and shows that they can, with a high degree of accuracy, identify the anonymous author of software, whether in source-code or binary form.
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Even Anonymous Coders Leave Fingerprints
Rachel Greenstadt, an associate professor of computer science at Drexel University, and Aylin Caliskan, Greenstadt's former PhD student and now an assistant professor at George Washington University, have found that code, like other forms of stylistic expression, are not anonymous. At the DefCon hacking conference Friday, the pair will present a number of studies they've conducted using machine learning techniques to de-anonymize the authors of code samples. Their work could be useful in a plagiarism dispute, for instance, but it also has privacy implications, especially for the thousands of developers who contribute open source code to the world.
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