acm-header
Sign In

Communications of the ACM

ACM TechNews

Image-Recognition Technology May Not Be as Secure as We Think


The special poster he's holding rendered the person at right invisible to image-classification software.

Image recognition technology may be more susceptible to deception than previously assumed.

Credit: Simen Thys, Wiebe Van Ranst, Toon Goedem/KU Leuven

Evidence is growing that image recognition technology may be more susceptible to deception than previously assumed.

Engineers at the ZeroFOX security startup suspected last year that a photo in a bogus social-media profile was modified to fool content filters, as a form of adversarial attack.

One senior technology executive said hacker groups are conducting "probing attacks" on social-media filters, with emphasis "on attacking [artificial intelligence] algorithms, changing a few pixels."

Researchers also demonstrated image- ecognition systems can be deceived offline, with a team from KU Leuven in Belgium successfully fooling popular image-classification software by masking themselves from a surveillance camera with a colorful poster.

Meanwhile, Wieland Brendel at the University of Tubingen in Germany publicly released a corpus of programming code that can be used to launch adversarial attacks on image-recognition systems, so developers of neural networks for image-recognition systems can test for flaws.

From The Wall Street Journal
View Full Article - May Require Paid Subscription

 

Abstracts Copyright © 2019 SmithBucklin, Washington, DC, USA


 

No entries found

Sign In for Full Access
» Forgot Password? » Create an ACM Web Account