Fox News correspondent Stephanie Bennett joins'Fox News Live' to break down recent evidence tying missile fragments in Russian attacks to North Korea. North Korea is putting surveillance cameras in schools and workplaces and collecting fingerprints, photographs and other biometric information from its citizens in a technology-driven push to monitor its population even more closely, a report said Tuesday. The state's growing use of digital surveillance tools, which combine equipment imported from China with domestically developed software, threatens to erase many of the small spaces North Koreans have left to engage in private business activities, access foreign media and secretly criticize their government, the researchers wrote. But the isolated country's digital ambitions have to contend with poor electricity supplies and low network connectivity. Those challenges, and a history of reliance on human methods of spying on its citizens, mean that digital surveillance isn't yet as pervasive as in China, according to the report, published by the North Korea-focused website 38 North. The study's findings align with widely held views that North Korean leader Kim Jong Un is stepping up efforts to tighten the state's control of its citizens and promote loyalty to his regime.

Amazon's Just Walk Out technology is touted as an AI-powered checkout system at its Fresh grocery stores, but new reports have claimed it used 1,000 people in India to monitor buyers. The company is now walking out on its own the technology that promised an innovative alternative to cashiers by using cameras and sensors to scan each item and is switching to a self-checkout shopping cart called Dash Cart. An Amazon spokesperson said they do have people watching cameras at Just Walk Out locations to annotate video images, but claimed the associates aren't monitoring customers. The Information first reported that Amazon's artificial intelligence technology just meant outsourcing hundreds of jobs overseas to workers who can watch you shop in real time. Amazon has referred to Just Walk Out as'a combination of sophisticated tools and technologies that added items to the shopper's'virtual cart' when they take an item off a shelf, and remove it when they put it back.

Robust and reliable anonymization of chest radiographs constitutes an essential step before publishing large datasets of such for research purposes. The conventional anonymization process is carried out by obscuring personal information in the images with black boxes and removing or replacing meta-information. However, such simple measures retain biometric information in the chest radiographs, allowing patients to be re-identified by a linkage attack. Therefore, there is an urgent need to obfuscate the biometric information appearing in the images. We propose the first deep learning-based approach (PriCheXy-Net) to targetedly anonymize chest radiographs while maintaining data utility for diagnostic and machine learning purposes. Our model architecture is a composition of three independent neural networks that, when collectively used, allow for learning a deformation field that is able to impede patient re-identification. Quantitative results on the ChestX-ray14 dataset show a reduction of patient re-identification from 81.8% to 57.7% (AUC) after re-training with little impact on the abnormality classification performance. This indicates the ability to preserve underlying abnormality patterns while increasing patient privacy. Lastly, we compare our proposed anonymization approach with two other obfuscation-based methods (Privacy-Net, DP-Pix) and demonstrate the superiority of our method towards resolving the privacy-utility trade-off for chest radiographs.

Back in 2021, a law took effect in New York City that requires businesses to post conspicuous signs if they're collecting customers' biometric information, such as their facial scans and fingerprints. Now, Amazon is facing a proposed class-action lawsuit that accuses the company of failing to inform customers at its Go cashierless stores that it was collecting their biometrics. In the lawsuit (PDF), filed by Alfredo Alberto Rodriguez Perez, the plaintiff argues that Go stores constantly use customers' biometrics "by scanning [their palms] to identify them and by applying computer vision, deep learning algorithms, and sensor fusion that measure the shape and size of each customer's body to identify customers, track where they move in the stores, and determine what they have purchased." It said the company only put up signs about its biometric tracking activities over a year after the law went into effect. Amazon's Go stores give shoppers the option to take whatever product they have off shelves and walk out without the need to check out.

The Texas attorney general sued Alphabet Google on Thursday, alleging the search giant violated state laws by collecting biometric data on face and voice features without seeking the full consent of users. Texas alleged Google's data-collection practices stretched back to 2015 and affected millions of the state's residents, according to a complaint filed in state district court in Midland County, Texas. A weekly digest of tech reviews, headlines, columns and your questions answered by WSJ's Personal Tech gurus. "Google's indiscriminate collection of the personal information of Texans, including very sensitive information like biometric identifiers, will not be tolerated," Texas Attorney General Ken Paxton said. "I will continue to fight Big Tech to ensure the privacy and security of all Texans."

We study the problem of extracting biometric information of individuals by looking at shadows of objects cast on diffuse surfaces. We show that the biometric information leakage from shadows can be sufficient for reliable identity inference under representative scenarios via a maximum likelihood analysis. We then develop a learning-based method that demonstrates this phenomenon in real settings, exploiting the subtle cues in the shadows that are the source of the leakage without requiring any labeled real data. In particular, our approach relies on building synthetic scenes composed of 3D face models obtained from a single photograph of each identity. We transfer what we learn from the synthetic data to the real data using domain adaptation in a completely unsupervised way. Our model is able to generalize well to the real domain and is robust to several variations in the scenes. We report high classification accuracies in an identity classification task that takes place in a scene with unknown geometry and occluding objects.

In 2020, a Canadian university employee named Ian Linkletter became increasingly alarmed by a new kind of technology that was exploding in use with the pandemic. It was meant to detect cheating by college and high-school students taking tests at home, and claimed to work by watching students' movements and analyzing sounds around them through their webcams and microphones to automatically flag suspicious behavior. So Linkletter accessed a section of the website of one of the anti-cheating companies, named Proctorio, intended only for instructors and administrators. He shared what he found on social media. Now Linkletter, who became a prominent critic of the technology, has been sued by the company. But he is not the only one.

Clearview AI has proposed to restrict sales of its faceprint database as part of a settlement with the American Civil Liberties Union (ACLU). The controversial facial recognition firm caused a stir due to scraping billions of images of people across the web without their consent. As a result, the company has faced the ire of regulators around the world and numerous court cases. One court case filed against Clearview AI was by the ACLU in 2020, claiming that it violated the Biometric Information Privacy Act (BIPA). That act covers Illinois and requires companies operating in the state to obtain explicit consent from individuals to collect their biometric data.

Notorious facial recognition company Clearview AI has agreed to permanently halt sales of its massive biometric database to all private companies and individuals in the United States as part of a legal settlement with the American Civil Liberties Union, per court records. Monday's announcement marks the close of a two-year legal dispute brought by the ACLU and privacy advocate groups in May of 2020 against the company over allegations that it had violated BIPA, the 2008 Illinois Biometric Information Privacy Act. This act requires companies to obtain permission before harvesting a person's biometric information -- fingerprints, gait metrics, iris scans and faceprints for example -- and empowers users to sue the companies who do not. "Fourteen years ago, the ACLU of Illinois led the effort to enact BIPA – a groundbreaking statute to deal with the growing use of sensitive biometric information without any notice and without meaningful consent," Rebecca Glenberg, staff attorney for the ACLU of Illinois, said in a statement. "BIPA was intended to curb exactly the kind of broad-based surveillance that Clearview's app enables. Today's agreement begins to ensure that Clearview complies with the law. This should be a strong signal to other state legislatures to adopt similar statutes."

Read on for CPW's highlights of the year's most significant events concerning biometric litigation, as well as our predictions for what 2022 may bring. One of the most critical consumer privacy statutes for biometric litigation has been Illinois' Biometric Information Privacy Act ("BIPA"), which regulates the collection, processing, disclosure, and security of the biometric information of Illinois residents. BIPA protects the "biometric information" of Illinois residents, which is any information based on "biometric identifiers" that identifies a specific person--regardless of how it is captured, converted, stored, or shared. Biometric identifiers are "a retina or iris scan, fingerprint, voiceprint, or scan of hand or face geometry." BIPA has found itself to be one of the most frequent targets for class actions, as it includes a private right of action with liquidated statutory damages, unlike many other data privacy statutes.