Plateshapez – Tool for Generating Adversarially Perturbed License Plate Overlays
Posted4 months agoActive4 months ago
github.comTechstory
controversialmixed
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Adversarial Machine LearningLicense Plate DetectionSurveillance
Key topics
Adversarial Machine Learning
License Plate Detection
Surveillance
A tool for generating adversarially perturbed license plate overlays was shared on GitHub, sparking a discussion about its potential misuse and implications for law enforcement and surveillance.
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Floxk AI is a startup that apparently runs highly suspicious police data collection services. As a fun bonus, it sells this data to private bidders and retains no liability for any mess-ups.
Apparently, it uses a Bluetooth system to relay some of this information. And seems to generally have awful security...
Any thoughts? Or further projects on this?
https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...
The real scandal seems to be the use of data brokers' data, re-selling/owning the data collected from publicly funded cameras, and also using bluetooth and ostensibly other outdated security.
I don't want to run the code, just show me some perturbed plates!
I can see this as being legal because it's still human readable.
Plate readers aren't expected to be 100% reliable as is (angles, lighting, network goes down, etc.) Plates get dirty, sometimes rusty. Also you can't test your own plate for machine readability against all the different types of systems cops use, so how could you reasonably know the issue is on your end and how to fix it?
Or trigger a human read of licence plate capture.