Computer-Generated Pattern Evades Surveillance Detection

A year-long research project has led to the development of a pattern that can evade surveillance cameras and license plate readers.

Bill Swearingen, the project's creator, has spent the past year testing and refining a computer-generated pattern that can block the detection of objects, people, or faces by surveillance cameras. The pattern, part of the noRecognition project, does not block video recording, but rather scrambles the camera's ability to identify and trigger alerts.

Swearingen's research builds on earlier work that showed it was possible to block camera detections. He started by incrementally defeating one open-source video camera detection algorithm after another, refining the patterns by scaling up his tests with additional computer processing power.

His proof of concept evolved into a reinforcement learning model, which trained itself on which patterns work and which do not against specific camera algorithms. Each time a pattern failed and an algorithm detected it, the model would try again, over and over, until it eventually defeated multiple algorithms at once.

Swearingen's model now creates new patterns every minute, each batch mathematically better than the last. On Friday, he demonstrated the pattern's effectiveness at the Def Con cybersecurity conference in Las Vegas, covering a 2009 Toyota Yaris with one of his newest patterns to see if the car would be invisible to detection by a Flock camera.

"We proved it was effective," Swearingen said, though the wheels were a challenge. The video of the demo will be out in the next few weeks.

The noRecognition project has a crowdsourcing campaign to help fund the sale of early merchandise featuring the patterns, from T-shirts to hoodies, with the potential for pattern-printed skins for vehicles down the line.

"Privacy is a fundamental right," Swearingen told TechCrunch in a call this week. He described his patterns as a way to allow people to 'opt out of being tracked.'

The project aims to make the patterns high quality and resolution good enough to work from a distance, while also looking aesthetically fashionable.

• Swearingen is keeping his strongest patterns off the internet to prevent the camera makers from defeating them, but the work is not yet done.

• His models are continuing to grind out new patterns, with every failure improving the model and the patterns getting better and better.

When asked about the potential impact of the project, Swearingen cited a personal experience where he felt uncomfortable and concerned about being tracked by surveillance cameras during a protest. He wanted to find a way to exercise his constitutional rights to free expression without being watched.

The noRecognition project is early proof that it is possible to avoid algorithmic detection in public spaces. The next step is getting the patterns into the hands of people who want them.

With a public demo in Las Vegas now under his belt, Swearingen is looking to the future and the potential for his patterns to be used by individuals who want to opt out of being tracked by surveillance cameras.