You Can Buy a Random Facial Recognition Photo on China’s Black Market for Just $.07

Summary

The undefined website reports on the sale of large datasets of facial recognition photos and personal information on China's black market for as little as $0.07 per image, raising concerns about identity theft and the security of facial recognition systems.

Abstract

The undefined website's "General Intelligence" section highlights a concerning trend in China where black-market sellers offer extensive packages of face images, with up to 20,000 images available for purchase at a cost as low as $0.07 each. These packages may also include deepfake-like software to animate still images for bypassing security measures on dating apps. The images and data are traded on platforms like Taobao and Xianyu, with transactions moving to messaging apps for sharing cloud storage links. This practice underscores the vulnerabilities in China's widespread use of facial recognition technology for identity verification by internet providers, social media apps, and banks. While advanced 3D face scanners on devices like the iPhone are less susceptible to such impersonation techniques, many smartphones lack these security features. The report also touches on the potential for identity theft in an era where biometric data is used as a password. Additionally, the website covers recent advancements in AI, including OpenAI's text-generating algorithm now being adapted to create images, NEC's improvements in facial recognition without manual labeling, and Nvidia's research on more realistic texture synthesis for video games.

Opinions

The sale of facial recognition data on the black market is a significant threat to personal security and privacy.
The low cost of these images underscores the ease of access to sensitive personal data.
The use of deepfake-like software to animate still images indicates a sophistication in methods used to deceive facial recognition systems.
The shift towards using facial recognition for identity verification across various services in China increases the potential impact of identity theft.
There is a recognition that while some high-end smartphones are equipped to resist such impersonation attempts, many devices are still vulnerable.
The article suggests that the U.S. may be less susceptible to these techniques due to reliance on smartphone authentication rather than app-based facial recognition.
The inclusion of AI research updates implies a connection between advancements in AI and the increasing sophistication of identity theft methods.

Sellers are offering packages of up to 20,000 face images.

Photo illustration. Photo: Tomohiro Ohsumi/Stringer/Getty Images

Welcome to General Intelligence, OneZero’s weekly dive into the A.I. news and research that matters.

A picture may be worth a thousand words, but apparently a picture of a face is only worth seven cents.

Black-market sellers in China are now offering packages of up to 20,000 face images and personal information data that can be used to impersonate others for as cheap as $0.07 each, or 0.5 yuan, according to a report from China’s state-owned news outlet Xinhua.

And it’s not just still images in these packages. For around $5, sellers will also provide deepfake-like software that animates a still image to bypass some security features on popular dating apps in China like Tantan. These apps require a person to nod or blink in order to verify that the phone isn’t being held up to a still image, according to a report on similar practices in the South China Morning Post.

These images are marketed on Chinese shopping websites like Taobao and Xianyu. When a buyer expresses interest, sellers then move the conversation to messaging apps like WeChat or QQ, where they share links to cloud storage drives with the images, data, and software to animate faces.

Much of China’s telecommunications infrastructure is being linked to facial recognition, meaning everyone from internet providers, social media apps, and banks are requiring face scans to verify a person’s identity as they use their devices. Being able to trick those systems would be basically assuming another person’s identity online.

It’s unlikely these impersonations would work on smartphones with 3D face scanners like the iPhone, which matches the topography of a person’s face rather than just an image. However, many mid-range and budget smartphones don’t have these kinds of sensors.

Most apps in the U.S. rely on the smartphone’s authentication, whether that be a fingerprint scanner or facial recognition like FaceID. The apps themselves do not attempt to perform facial recognition, making it less likely that these techniques would work as well in the States.

Everyone from internet providers, social media apps, and banks are requiring face scans to verify a person’s identity.

But these packages, including face photos, ID and phone numbers, and banking information, are a glimpse at what identity theft looks like in a world where your face is your password.

And now, here’s some of the most interesting A.I. research of the week:

OpenAI’s Text-Generating Algorithm Learns To Make Images

OpenAI’s GPT-2 algorithm is an enormous neural network that was able to analyze hundreds of millions of texts and spit out its own bits of writing. Seeded with a sentence, it could write a pretty haunting short story. Now, OpenAI is turning to the same algorithm to generate images, in an shockingly successful experiment.

NEC Ups Its Facial Recognition Chops

Facial recognition datasets are typically labeled images of people’s faces, meaning that if you have four photos of me, each is tagged with my name or some other identifier. But making these datasets by tagging every photo is time consuming. NEC has proposed a way to build large-scale facial recognition datasets without needing to label each identity or face. It uses a second algorithm to guess which faces are the same in a batch of millions of unlabeled images, and then adds those images with “pseudo-labels” into the original dataset.

Nvidia’s Play For More Realistic Video Games

Textures make video games look good. New research by Nvidia allows an algorithm to create realistic textures with life-like variation, a stepping-stone for A.I. able to create better virtual worlds in video games.