Breaking The Creepy AI in Police Cameras

[VIDEO] Benn Jordan did a great video on this. People on here regularly bash the EU's GDPR, but blocking this kind of corporate-driven police state is a heavy point in its favor.

For a video overview of this stuff: “Breaking The Creepy AI in Police Cameras”, Benn Jordan [36min, 1.7m views, 9d ago] [VIDEO]

Background: from this video ( [VIDEO] ) 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?

Ok Before I am accused of misrepresenting things and in the interest of clarity. 1. I am in San Francisco. 2. Upon further research Flock does not appear to be used by SFPD for ticketing. They have another camera system for that. That does not mean that Flock could not be used for speeding tickets or a host of other things like running red lights, littering etc. Microprocessors and CMOS cameras can do amazing things. Regardless of what company is doing the surveillance the debate remains the same. 1. Pervasive surveillance has the potential to be used inappropriately by authorities. Discussion is needed. 2. The data collected by a company such as Flock but not necessarily Flock could be used inappropriately or sold for other purposes. Benn Jordan has a good video on the subject [VIDEO] 3. The claim that Flock is responsible for %10 of solved cases seems dubious but without data it is difficult to know or believe. Given that Flock is in YC's portfolio makes it even more suspect. Flock or a company like Flock may try and become pervasive and indispensable before a public discussion places any limits on their behavior.

"Find Nearby Automated License Plate Readers (ALPR)" (70 comments), [LINK] Adversarial computer vision and DIY OSS $250 RPi Hailo ALPR (2M views), [VIDEO] "Tire Pressure Sensor IDs: Why, Where and When (2015)" (30 comments), [LINK]

Local strategies, "The Cameras Tracking You Are a Security Nightmare" (90 comments), [LINK] "Find Nearby Automated License Plate Readers (ALPR)" (70 comments), [LINK] Adversarial computer vision and DIY OSS $250 RPi Hailo ALPR (2M views), [VIDEO] "Tire Pressure Sensor IDs: Why, Where and When (2015)" (30 comments), [LINK]

Same author talked about adversarial license plates that trick these cameras with a sequence of black blocks, discussed here in original form [1]. He is interested in breaking both the plate detection (ideal) and character recognition (good). The examples are pretty cool looking. [1]: [VIDEO]

Sure, around 33:00 here: [LINK] The other video is [VIDEO] but I don't recall which one goes more into it. It's also possible I'm just remembering Flock-specific stuff from other sources, and the things he shows in these videos are more general issues with security camera companies (using Flock as the example). It would be great if this stuff was (also?) published as blog posts so that it could be easily skimmed...

Just a reminder here of this experiment using adversarial techniques to confuse the license plate readers. Just an experiment, may not be legal in all locations, check your local laws. [VIDEO]

Musician-turning-tech anarchist (?) Benn Jordan is making a very interesting series of videos about Flock cameras, their poor safety, and their gray-area interfacing with local governments: [LINK] [LINK] [LINK] [VIDEO] I recommend them.

It's rational to oppose Flock cameras in particular, while admitting that secure publicly accountable camera use for police purposes may have a legitimate place. YouTuber Benn Jordan did a pretty decent break down of how Flock is not that. [VIDEO]

Funny you should mention this. Benn Jordan, on the heels of his Flock camera research, reverse engineered a non-flock ALRP unit and built his own system using some off the shelf parts, a tablet, and 3D printer. He did it mostly as an experiment but also due to the fact that Flock's algorithm for image detection is astoundingly bad and has a high incident of reading plates incorrectly. There are a handful of open-source models for license plate detection, I forget exactly which model outperformed the rest, but it was an excellent watch and help me really understand just how inefficient these commercial systems are and how easy they can be to defeat: [VIDEO]