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AIQuiet 14d · day 14

Adversarial Fashion Garments Disrupt AI Surveillance Systems

Companies sell clothing designed to confuse facial recognition and object detection, amid growing backlash against AI-powered surveillance.

What to know

  • Companies Cap_able and Urban Privacy are selling garments with adversarial patterns designed to confuse facial recognition and object detection systems.
  • Patterns were developed by cybersecurity expert Bill Swearingen and tested against 11 object detection models; they work by lowering confidence scores or generating false detections.
  • The trend reflects mounting public backlash against AI-powered surveillance systems citing lack of consent, unclear data storage and use, and misuse risks.
  • Designers frame adversarial fashion as statement-making about surveillance rather than a reliable privacy solution.

The dispute Whether adversarial fashion represents meaningful privacy protection or primarily serves as artistic commentary on surveillance culture. · positions read across 11 posts and comments

many voices

Adversarial fashion is an important statement and symbol of resistance to mass surveillance.

  • “Privacy is a human right, and the popularity of this just goes to show that people are interested in preserving their privacy.”

    Bill Swearingen · IEEE Spectrum ↗
some voices

This is a creative but ultimately limited approach—the real issue is the arms race between adversarial techniques and AI systems.

  • “AI trying to break AI is the next cybersecurity hamster wheel (which is spinning already)… this is about making a statement instead of being a serious privacy solution.”

    timokissel@mastodon.world · Mastodon ↗

Bill Swearingen Cybersecurity expertRachele Didero Cap_able founder, assistant professorDaniel Preuß Urban Privacy cofounderCap_able Clothing companyUrban Privacy Fashion company

How it unfolded 1 development · click the chart to see its coverage articlesposts

Peak 6 pieces in 3h at Sep 14, 11 AM; 14 pieces over 14 days (2 articles · 2 posts · 10 comments) Sep 14, 8 AM — 3 pieces · 2 articles · 1 post — Mastodon 1, Hacker News 1, Newswires 1Sep 14, 11 AM — 6 pieces · 1 post · 5 comments — Hacker News 5, Mastodon 1Sep 14, 2 PM — 2 pieces · 2 comments — Hacker News 2Sep 14, 5 PM — 2 pieces · 2 comments — Hacker News 2Sep 14, 8 PM — quietSep 14, 11 PM — 1 piece · 1 comment — Hacker News 1Sep 15, 2 AM — quietSep 15, 5 AM — quietSep 15, 8 AM — quietSep 15, 11 AM — quietSep 15, 2 PM — quietSep 15, 5 PM — quietSep 15, 8 PM — quietSep 15, 11 PM — quietSep 16, 2 AM — quietSep 16, 5 AM — quietSep 16, 8 AM — quietSep 16, 11 AM — quietSep 16, 2 PM — quietSep 16, 5 PM — quietSep 16, 8 PM — quietSep 16, 11 PM — quietSep 17, 2 AM — quietSep 17, 5 AM — quietSep 17, 8 AM — quietSep 17, 11 AM — quietSep 17, 2 PM — quietSep 17, 5 PM — quietSep 17, 8 PM — quietSep 17, 11 PM — quietSep 18, 2 AM — quietSep 18, 5 AM — quietSep 18, 8 AM — quietSep 18, 11 AM — quietSep 18, 2 PM — quietSep 18, 5 PM — quietSep 18, 8 PM — quietSep 18, 11 PM — quietSep 19, 2 AM — quietSep 19, 5 AM — quietSep 19, 8 AM — quietSep 19, 11 AM — quietSep 19, 2 PM — quietSep 19, 5 PM — quietSep 19, 8 PM — quietSep 19, 11 PM — quietSep 20, 2 AM — quietSep 20, 5 AM — quietSep 20, 8 AM — quietSep 20, 11 AM — quietSep 20, 2 PM — quietSep 20, 5 PM — quietSep 20, 8 PM — quietSep 20, 11 PM — quietSep 21, 2 AM — quietSep 21, 5 AM — quietSep 21, 8 AM — quietSep 21, 11 AM — quietSep 21, 2 PM — quietSep 21, 5 PM — quietSep 21, 8 PM — quietSep 21, 11 PM — quietSep 22, 2 AM — quietSep 22, 5 AM — quietSep 22, 8 AM — quietSep 22, 11 AM — quietSep 22, 2 PM — quietSep 22, 5 PM — quietSep 22, 8 PM — quietSep 22, 11 PM — quietSep 23, 2 AM — quietSep 23, 5 AM — quietSep 23, 8 AM — quietSep 23, 11 AM — quietSep 23, 2 PM — quietSep 23, 5 PM — quietSep 23, 8 PM — quietSep 23, 11 PM — quietSep 24, 2 AM — quietSep 24, 5 AM — quietSep 24, 8 AM — quietSep 24, 11 AM — quietSep 24, 2 PM — quietSep 24, 5 PM — quietSep 24, 8 PM — quietSep 24, 11 PM — quietSep 25, 2 AM — quietSep 25, 5 AM — quietSep 25, 8 AM — quietSep 25, 11 AM — quietSep 25, 2 PM — quietSep 25, 5 PM — quietSep 25, 8 PM — quietSep 25, 11 PM — quietSep 26, 2 AM — quietSep 26, 5 AM — quietSep 26, 8 AM — quietSep 26, 11 AM — quietSep 26, 2 PM — quietSep 26, 5 PM — quietSep 26, 8 PM — quietSep 26, 11 PM — quietYesterday, 2 AM — quietYesterday, 5 AM — quietYesterday, 8 AM — quietYesterday, 11 AM — quietYesterday, 2 PM — quietYesterday, 5 PM — quietYesterday, 8 PM — quietYesterday, 11 PM — quiet 1
Sep 15Sep 16Sep 17Sep 18Sep 19Sep 20Sep 21Sep 22Sep 23Sep 24Sep 25Sep 26now · 2:00 AM ET
  1. 1

    IEEE Spectrum reports on commercial adversarial fashion lines and broader surveillance backlash

    Coverage details Cap_able and Urban Privacy selling garments with adversarial patterns, and traces the broader movement against AI surveillance systems including ALPR mapping projects and property damage. Cap_able's dresses, pants, and tops use jacquard-woven patterns; Urban Privacy's Faception Reloaded collection uses black-and-white facial abstractions to fool detectors.

    “If we're able to camouflage a person as something else, then we're obtaining our goal. We use this very visible and tangible item to talk about something that most of the time is intangible.”
    — Rachele Didero
    1. first by HN Frontpage, 13d ago

    • timokissel@mastodon.world

      # AI trying to break AI is the next # cybersecurity hamster wheel (which is spinning already). Also, loving this intersection of # technology and # fashion ! Funny how the machines are now dressing us, and kidding aside, this is about making a statement instead of being a serious # privacy solution. https:// spectrum.ieee.org/adversarial- fashion

      timokissel@mastodon.worldMastodon13d ago7▲view on Mastodon ↗
    2 more of the top 3 · 11 posts in this stretch
    • There is a weak component to facial recognition systems that can be exploited to make one invisible to facial recognition, but you stick out like a sore thumb to people. The exploit is to not have a human face, meaning the regular pattern of two eyes centered above a nose and mouth. The exploit is as simple as placing a sticker of a 3rd eye, a 2nd…

      bsenftnerHacker News13d agoview on Hacker News ↗
    • Anyone else think of "A Scanner Darkly" movie with the interpolate mask that transitions between different faces as the means for better Adversarial Fashion?Wouldn't one be able to use a hyper real mask to create false evident to frame someone? People are so blind in trusting AI that innocent people are being left in jail were primitive detective…

      yndoendoHacker News13d agoview on Hacker News ↗
    all of them →
  2. background

    noRecognition Kickstarter project debuts at DEF CON hacker convention — Adversarial fashion project noRecognition is presented at DEF CON, showcasing patterns designed to evade surveillance cameras. Swearingen's patterns have been tested against 11 object detection models—four that search faces, two that recognize faces, and five that detect people.

  3. background

    Bill Swearingen develops adversarial patterns using reinforcement learning — Cybersecurity expert Swearingen creates a Python-based fuzzer targeting YOLO object detection frameworks, then develops a reinforcement learning algorithm to generate adversarial patterns that confuse facial recognition and object detection systems.

What people are saying 7 voices from 1 site · best of 11 · verbatim