A cybersecurity researcher named Bill Swearingen has developed computer-generated patterns that, when applied to clothing or vehicles, prevent surveillance cameras and licence plate readers from detecting people or objects covered by them. Rather than blocking cameras from recording, the patterns, part of a project called noRecognition, scramble the detection algorithms so no alert is triggered, effectively letting the wearer disappear from automated tracking systems. The work highlights growing public concern over the spread of algorithmic surveillance and offers a countermeasure that people can use to reclaim some privacy.

Swearingen, based in Kansas City and co-founder of the SecKC cybersecurity meet-up, ran roughly 31 million tests over the past year to refine patterns capable of defeating commonly used surveillance technology. He first demonstrated the approach publicly on a vehicle at the Def Con cybersecurity conference in Las Vegas, proving it could work in real-world conditions. He said the project was partly inspired by wanting to attend a protest without being tracked, and builds on earlier efforts, including adversarial clothing and eyewear, that have tried with varying success to defeat facial recognition systems.