noRecognition: Could a Pattern on Clothing Fool Facial Recognition?
Bill Swearingen
DEF CON 34 · Day 1 · Main Stage
In his compelling DEF CON talk, "noRecognition: Could a Pattern on Clothing Fool Facial Recognition?", Bill Swearingen, a security researcher from SecKC, delves into the critical and rapidly escalating issue of mass surveillance in the United States. Swearingen meticulously details his year-long research into **adversarial patterns** designed to disrupt and confuse modern AI-powered camera systems, specifically targeting **facial recognition** and **person/face detection**. The core premise explores whether a strategically designed pattern, when worn on clothing, can render an individual effectively invisible or unidentifiable to these pervasive surveillance technologies.
AI review
Solid adversarial ML research with real-world motivation and a genuinely impressive scale of testing (31.7 million patterns). The DRL evolution engine is clever, the community compute collaboration is peak DEF CON, and the Flock Safety framing gives it teeth. Falls short of 5 because the physical validation gap is significant—this is still mostly simulation work claiming real-world applicability.