● Covered by 1 source · 1 reportMedium impact1 neutral
New Adversarial Pattern Blocks Surveillance Camera Detection
Key points
- noRecognition pattern blocks surveillance camera detection.
- Pattern prevents identification of objects, people, or faces.
- Successfully demonstrated at Def Con cybersecurity conference.
- Developed over 31 million tests to achieve effectiveness.
New Anti-Surveillance Technology Developed
Bill Swearingen has created a computer-generated pattern, called noRecognition, designed to prevent surveillance cameras from detecting individuals and objects. After a year of development and 31 million tests, the pattern can be applied to clothing or vehicles to scramble the detection capabilities of commonly deployed license plate readers and surveillance cameras.
How noRecognition Works
The noRecognition pattern does not prevent cameras from recording video footage. Instead, it interferes with the camera's ability to identify objects, people, or faces, thereby preventing detection alerts. This effectively makes the covered subject undetectable by automated surveillance algorithms, requiring manual review to identify them.
Public Demonstration and Impact
The technology was publicly demonstrated at the Def Con cybersecurity conference in Las Vegas, where a vehicle with the pattern successfully evaded surveillance detection. Swearingen states that the project aims to provide a way for people to opt-out of algorithmic surveillance and automatic tracking, citing privacy as a fundamental right.
Context of Modern Surveillance
Modern surveillance cameras often incorporate advanced detection algorithms for tasks like license plate tracking and facial recognition. These algorithms allow law enforcement to sift through large amounts of footage for specific activities. The noRecognition pattern offers a countermeasure to these automated detection systems.
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Reporting from
Bill Swearingen developed a computer-generated pattern, named noRecognition, that prevents common license plate readers and surveillance cameras from detecting objects or people it covers. This technology allows individuals to avoid automatic detection by algorithmic surveillance systems, offering a method to opt-out of tracking.