Lucene search

K
schneierBruce SchneierSCHNEIER:AE73E75E60E9583A7DFF23D95DB4C27A
HistoryAug 13, 2018 - 9:02 p.m.

Identifying Programmers by their Coding Style

2018-08-1321:02:18
Bruce Schneier
www.schneier.com
55
programmer identification
coding style
de-anonymizing code
privacy implications
open source contributers
machine learning techniques

Fascinating research 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.