Identifying Programmers by Their Coding Style
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Fascinating research on de-anonymizing code—from either source code or compiled code:
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.
Tags: de-anonymization, machine learning, plagiarism, privacy
Sidebar photo of Bruce Schneier by Joe MacInnis.
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