Malicious coders will lose anonymity as identity-finding research matures

ADELPHI, Md. (Jan. 15, 2016) — Literature critics may know a writer by his style, in the same way a chunk of computer code is identified through a machine learning algorithm according to its writer’s nuances.Writing style extends beyond prose, so that even in computer languages you could attribute work to its author in minutes with near perfect accuracy – in a lab.That is what a team of university students tested during their time at the U.S. Army Research Laboratory, or ARL, said Richard Harang, ARL network security researcher and technical lead. “A tool kit that may one day help analysts to identify malware authors more quickly.”The code stylometry study that was presented by Aylin Caliskan-Islam at the 32nd Chaos Computer Conference looked at samples from 1,600 coders and, with…


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