# Facial recognition Published articles for Facial recognition. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Hackers steal and publish data on 41,000 Homeland Security workers DevFeed: [Hackers steal and publish data on 41,000 Homeland Security workers]() Original publisher: [Read original article]() Author: Danny Bradbury Published: 2026-10-30T11:33:12Z Content type: news Language: en Sources: [Malwarebytes]() Topics: [Security](), [enterprise data protection](), [Single sign-on (SSO)](), [Access Control](), [credential-based attacks](), [Security, Privacy and Abuse Prevention]() Tags: [account](), [active-directory](), [breach](), [cisa](), [credentials](), [cybersecurity](), [data](), [data-breach](), [data-breaches](), [dataset](), [dhs](), [dump](), [email](), [employees](), [facial-recognition](), [groups](), [guidance](), [hackers](), [privacy](), [security](), [work](), [workers]() ### AI overview Hackers published work contact details and internal group memberships for more than 41,000 DHS workers across nearly 7,000 offices, including ICE, CBP, and CISA staff. The records could help attackers target employees with convincing messages or enable harassment and threats; some group memberships identify access to sensitive tools or roles. The Department of Peace says it obtained the data through DHS's Okta single sign-on service, but Okta reports no evidence its systems were compromised, and DHS says it is aware of a potential breach. It remains unclear whether the leak has led to threats or affected operations. DHS employees are advised to follow agency guidance, verify unexpected contact through trusted channels, avoid sharing passwords or MFA codes, change reused personal passwords, enable MFA where available, and report suspicious contact or threats to agency security. ### Source excerpt A hacker group claims it stole data on 41,000 DHS employees, exposing work contact details and internal group memberships. ## GhostFaceMPC: Privacy-Preserving Face Recognition with Multi-Party Computation DevFeed: [GhostFaceMPC: Privacy-Preserving Face Recognition with Multi-Party Computation]() Original publisher: [Read original article]() Author: Davide Carnemolla, Dario Catalano, Mario Di Raimondo Published: 2026-10-22T04:00:00Z Content type: article Language: en Sources: [arXiv: Cryptography and Security]() Topics: [Facial recognition](), [Security & Privacy](), [Neural Network](), [quantization]() Tags: [circuit](), [cs-cr](), [face-recognition](), [facial-recognition](), [matching](), [network](), [privacy](), [quantization](), [security]() ### AI overview GhostFaceMPC applies secure multi-party computation to face recognition, covering feature extraction, storage and matching without exposing raw images or biometric embeddings at any stage. The paper describes a quantization of GhostFaceNet designed for MPC and circuit optimizations intended to make this processing practical. The supplied excerpt does not report performance measurements or implementation requirements. ### Source excerpt arXiv:2610.29987v1 Announce Type: new Abstract: Facial recognition has become central to modern authentication systems, security frameworks, and personalized services. However, its widespread adoption is hindered by severe privacy risks, particularly surrounding unauthorized access to sensitive biometric data. To address these challenges, this paper presents GhostFaceMPC, the first end-to-end, privacy-preserving face recognition system to evaluate a deep convolutional neural network extractor and matching under secure multi-party computation. GhostFaceMPC enables secure processing of facial data across all stages of a face recognition process, from feature extraction and storage to matching, without exposing raw images or biometric embeddings at any stage. We introduce a multi-party computation-friendly quantization of the GhostFaceNet model and circuit optimizations that make face recognition under multi-party computation practical. The code is available at https://github.com/crypto-unict/GhostFaceMPC. ## Surveillance Company Tells Cops It Wants to Add Facial Recognition to Flock Cameras DevFeed: [Surveillance Company Tells Cops It Wants to Add Facial Recognition to Flock Cameras]() Original publisher: [Read original article]() Author: EditorDavid Published: 2026-10-04T00:21:00Z Content type: news Language: en Sources: [Slashdot]() Topics: [Facial recognition](), [real-time face tracking]() Tags: [ai](), [facial-recognition](), [privacy](), [security](), [surveillance]() ### AI overview VIDIZMO promotes adding facial recognition and other analysis to footage from Flock cameras, although it has not yet built the advertised export integration or begun processing that footage. Its CEO says the company would like to integrate with Flock, and VIDIZMO also describes demographic analysis for marketing based on people's race or age. ### Source excerpt 404 Media reports: "We will not add facial recognition to our devices," Flock CEO Garrett Langley said in a recent video. But other, third-party companies are telling cops that they are willing to add facial recognition to data gathered by Flock cameras in order to "close that gap." A company called VIDIZMO is advertising the capability to export footage from FlockOS to its own platforms that do facial recognition, behavior prediction, and racial and gender analysis on live camera feeds. VIDIZMO is a several decades-old video analysis and database company that has started offering facial recognition technology to cops within the last six months. In a May email to Johnson City, Tennessee, deputy police chief Michael Adams, a salesperson from VIDIZMO wrote that the company's product could do facial recognition on both Flock and Axon [body-worn camera] data in "one searchable platform...." VIDIZMO's CEO, Nadeem Khan, told 404 Media on a video call that the company has not yet started running facial recognition tech on footage from Flock cameras, and that it has not actually built the specific tool that would export data from Flock's system to its own platform (though the company advertises this capability online, and the company already sells other facial recognition products). But Khan said VIDIZMO "would love to do the integration," and that he believes facial recognition "is the way the world is going, the way the world will have to be," and that he thinks Flock should offer the capability itself in a way that "balances privacy, security, and the freedom that we enjoy in this country." The article notes that VIDIZMO says on its website, "You can identify individuals from seven races: White, Black, Indian, East Asian, Southeast Asian, Middle Eastern, and Latino Hispanic." VIDIZMO adds that stores or cities can also then do "demographic analysis" for marketing purposes by determining the races or ages of people showing up.... Read more of this story at Slashdot. ## Podcast: The FBI Was Hacked. We've Seen the Data DevFeed: [Podcast: The FBI Was Hacked. We've Seen the Data]() Original publisher: [Read original article]() Author: Joseph Cox Published: 2026-10-02T17:37:35Z Content type: news Language: en Sources: [404 Media]() Topics: [Security](), [Facial recognition]() Tags: [404-media](), [ai](), [breach](), [facial-recognition](), [fbi](), [flock](), [meta](), [podcast](), [podcasts](), [spotify](), [youtube]() ### AI overview The podcast discusses the FBI employee data breach, a proposal to add facial recognition to Flock camera data, and reporting that some tasks attributed to Muse, Meta's agentic AI, are performed by people. ### Source excerpt The massive FBI hack; a company wants to add facial recognition onto Flock; and Muse in some cases is actually just people. ## Edge Computing and Security for Access Control Applications: Getting the Best of the Two Worlds DevFeed: [Edge Computing and Security for Access Control Applications: Getting the Best of the Two Worlds]() Original publisher: [Read original article]() Author: Arrow Electronics, Microchip Published: 2026-10-01T14:01:12Z Content type: article Language: en Sources: [EE Times]() Topics: [Access Control](), [Security](), [Jetson]() Tags: [analog](), [analysis](), [business](), [community](), [designline](), [digital](), [edge-computing](), [education](), [ee-times](), [ee-times-university](), [eelife](), [eelive-electronic-design](), [eet](), [electrical-engineering](), [electronic-components](), [electronic-engineering-times](), [electronics](), [embedded](), [embedded-systems](), [facial-recognition](), [fundamentals-courses](), [learning](), [mixed-signal](), [news](), [opinion](), [part-search](), [product-search](), [security](), [semiconductors](), [sensitive-data](), [software](), [spoofing](), [tech-papers](), [technology](), [video](), [webinars-plus-bitcasts]() ### AI overview A webinar describes an access control solution that runs facial recognition and liveness detection on a 32-bit MPU with one RGB camera and hardware cryptography. It covers real-time edge AI, on-device processing, protection of sensitive facial data, spoofing prevention, and deployment across buildings, vehicles, and appliances. ### Source excerpt Join us where attendees will see how on-device processing improves resilience, reduces exposure of sensitive data, counters spoofing, and supports practical deployment across buildings, smart locks, vehicles and appliances. The post Edge Computing and Security for Access Control Applications: Getting the Best of the Two Worlds appeared first on EE Times. ## UK rail cops' GBP 320K face-scanning spree nets zero matches DevFeed: [UK rail cops' GBP 320K face-scanning spree nets zero matches]() Original publisher: [Read original article]() Author: Carly Page Published: 2026-09-30T08:30:00Z Content type: news Language: en Sources: [theregister]() Topics: [Facial recognition]() Tags: [facial-recognition](), [false-positive](), [police](), [security](), [uk]() ### AI overview British Transport Police's six-month facial recognition pilot generated one alert, which was a false positive. The supplied summary reports no confirmed matches. ### Source excerpt British Transport Police's six-month facial recognition pilot produced one alert, and it was a false positive ## Surveillance Company Tells Cops It Wants to Add Facial Recognition to Flock Cameras DevFeed: [Surveillance Company Tells Cops It Wants to Add Facial Recognition to Flock Cameras]() Original publisher: [Read original article]() Author: Jason Koebler Published: 2026-09-29T13:53:42Z Content type: news Language: en Sources: [404 Media]() Topics: [Facial recognition](), [ACR]() Tags: [cameras](), [facial-recognition](), [flock](), [privacy](), [privacy-security](), [surveillance]() ### AI overview VIDIZMO is pitching police departments on adding facial recognition and other analysis to data from Flock cameras, despite Flock's statement that it will not add facial recognition. The company advertises exporting FlockOS footage to its platform, but its CEO said it has not built that specific integration or begun running facial recognition on Flock footage. ### Source excerpt A surveillance company wants to "close the gap" that Flock won't do, by pitching facial recognition on its cameras. ## The End of Privacy Is Here (with Kashmir Hill) DevFeed: [The End of Privacy Is Here (with Kashmir Hill)]() Original publisher: [Read original article]() Author: Joseph Cox Published: 2026-09-28T13:37:16Z Content type: opinion Language: en Sources: [404 Media]() Topics: [Security & Privacy](), [Facial recognition]() Tags: [ai](), [facial-recognition](), [podcast](), [privacy](), [surveillance](), [surveillance-cameras]() ### AI overview Joseph speaks with New York Times reporter Kashmir Hill about facial recognition in surveillance cameras and smart glasses, viral accounts using the technology to identify people and expose personal information, and the implications for privacy. ### Source excerpt Facial recognition is everywhere now. Soon it's going to be right in your face, too. ## Machine vision company Cognex buys Intel robotics spinoff RealSense for $600M DevFeed: [Machine vision company Cognex buys Intel robotics spinoff RealSense for $600M]() Original publisher: [Read original article]() Author: Mike Wheatley Published: 2026-09-22T23:42:48Z Content type: news Language: en Sources: [SiliconANGLE]() Topics: [Computer vision](), [Robotics](), [intel](), [3D](), [Facial recognition]() Tags: [3d](), [acquisition](), [autonomous-robots](), [cameras](), [cognex](), [computer-vision](), [depth-cameras](), [depth-perception](), [emerging-tech](), [facial-recognition](), [intel](), [machine-vision](), [news](), [physical-ai](), [realsense](), [robotic-perception](), [robotics](), [spinoff](), [the-latest](), [transaction](), [vision]() ### AI overview Cognex plans to acquire Intel robotics spinoff RealSense in a deal valued at about $600 million. RealSense develops depth cameras, 3D scanning, and gesture and facial recognition technologies used in robotics, mapping, security, and touchless devices. ### Source excerpt U.S. machine vision company Cognex Corp. said today that it intends to buy RealSense Inc., the robotics and computer vision startup that was spun out of Intel Corp. 14 months earlier in a deal valued at around $600 million. Nasdaq-listed Cognex will pay around $500 million in cash for the startup, while providing a three-year [...] The post Machine vision company Cognex buys Intel robotics spinoff RealSense for $600M appeared first on SiliconANGLE. ## Viral AI actress' hotline face-scans every caller, watches their mood DevFeed: [Viral AI actress' hotline face-scans every caller, watches their mood]() Original publisher: [Read original article]() Author: Ax Sharma Published: 2026-09-19T11:38:20Z Content type: news Language: en Sources: [BleepingComputer]() Topics: [Artificial Intelligence](), [Google]() Tags: [ai](), [camera](), [computer-help](), [computer-security](), [computers](), [face-id](), [facial-recognition](), [gemini](), [google](), [identity-verification](), [infosec](), [infosec-computer-security](), [legal](), [linux](), [mac](), [malware](), [malware-removal](), [news](), [privacy](), [recording](), [safety](), [security](), [spyware](), [support](), [tech-support](), [technical-support](), [tilly-norwood](), [virus](), [virus-removal](), [voice](), [windows](), [workplace]() ### AI overview An investigation of the Talking Tilly AI video-call service finds that callers must undergo an automated age check using a video selfie or government ID, while the service analyzes camera footage and voice to infer mood. Calls are recorded and processed by external providers, and an automated safety classifier incorrectly withheld one test recording. ### Source excerpt AI actress Tilly Norwood went viral after glitching into Chinese on Piers Morgan Uncensored last night. Her "Talking Tilly" video call service face-scans every caller for an 18+ age check, senses callers' moods during calls, and shuts down permanently on September 27. We tried it and read the fine print. [...] ## Calling viral AI actress Tilly Norwood? Agree to a face scan first DevFeed: [Calling viral AI actress Tilly Norwood? Agree to a face scan first]() Original publisher: [Read original article]() Author: Ax Sharma Published: 2026-09-19T11:38:20Z Content type: news Language: en Sources: [BleepingComputer]() Topics: [Artificial Intelligence](), [service](), [systems](), [Google]() Tags: [ai](), [computer-help](), [computer-security](), [computers](), [face-id](), [facial-recognition](), [gemini](), [google](), [identity](), [identity-verification](), [infosec](), [infosec-computer-security](), [linux](), [mac](), [malware](), [malware-removal](), [privacy](), [recording](), [safety](), [security](), [service](), [spyware](), [support](), [tech-support](), [technical-support](), [tilly-norwood](), [times](), [video](), [virus](), [virus-removal](), [windows]() ### AI overview An investigation of the Talking Tilly video-call service finds that callers must complete an automated age check using a video selfie or, if necessary, a government ID. The service also analyzes camera feeds and voice tone for mood, records and transcribes calls, and uses automated moderation that can produce false abuse flags. ### Source excerpt AI actress Tilly Norwood went viral after glitching into Chinese on Piers Morgan Uncensored last night. Her "Talking Tilly" video call service face-scans every caller for an 18+ age check, senses callers' moods during calls, and shuts down permanently on September 27. We tried it and read the fine print. [...] ## Tennessee woman sues Fargo after facial recognition linked her to a bank fraud investigation DevFeed: [Tennessee woman sues Fargo after facial recognition linked her to a bank fraud investigation]() Original publisher: [Read original article]() Author: Rob Thubron Published: 2026-09-17T13:26:00Z Content type: news Language: en Sources: [TechSpot]() Topics: [Facial recognition](), [incident](), [Software]() Tags: [2025](), [children](), [crime](), [facial-recognition](), [fraud-investigation](), [lawsuit](), [news](), [results](), [security](), [surveillance](), [tech-culture](), [us]() ### AI overview A Tennessee grandmother was arrested after facial recognition software identified her as a possible match in a North Dakota bank fraud investigation. She spent 108 days in jail before evidence showed she was in Tennessee, and she has since sued the City of Fargo and a detective. ### Source excerpt In July 2025, a team of US Marshals arrested 50-year-old Lipps in Tennessee at gunpoint while she was babysitting four young children. She was booked into the county jail in Tennessee as a fugitive from justice wanted in North Dakota. Read Entire Article ## 25 Years of Mass Surveillance Is Enough DevFeed: [25 Years of Mass Surveillance Is Enough]() Original publisher: [Read original article]() Author: Bruce Schneier Published: 2026-09-15T11:01:41Z Content type: opinion Language: en Sources: [Schneier on Security]() Topics: [Security](), [systems](), [Artificial Intelligence](), [Internet](), [Facial recognition]() Tags: [ai](), [attacks](), [facial-recognition](), [fbi](), [government](), [internet](), [law-enforcement](), [national-security](), [privacy](), [security](), [surveillance](), [uncategorized]() ### AI overview This essay argues that surveillance expanded from targeted monitoring after September 11 to routine mass collection by governments, private companies, and security systems. It examines how data from technology companies and brokers flows to law enforcement and how AI-driven surveillance may intensify the associated problems. ### Source excerpt This essay was written with Cindy Cohn, and originally appeared in Lawfare. One of the many legacies of the terrorist attacks of Sept. 11 is the government-wide shift from targeted surveillance--such as individual wiretaps or pen register/trap and trace orders--to mass surveillance techniques--such as tapping into the internet backbone or mass collection of telephone or internet metadata. The legal and technical architecture of modern mass surveillance, initially framed as a necessary defense against terrorist threats, has grown far beyond that justification and national security in general. Mass surveillance is now a routine tool used by law enforcement. ICE uses it in... ## Frequently Asked Questions about FHE DevFeed: [Frequently Asked Questions about FHE]() Original publisher: [Read original article]() Published: 2025-07-18T17:31:49Z Content type: article Language: en Sources: [Jeremy Kun]() Topics: [homomorphic encryption](), [FHE](), [Cryptography](), [Mathematics](), [GPU](), [Facial recognition](), [Sorting]() Tags: [cryptography](), [encryption](), [facial-recognition](), [fhe](), [gpu](), [homomorphic-encryption](), [mathematics](), [programming]() ### AI overview A collection of short answers about fully homomorphic encryption (FHE), covering encrypted queries, computation on ciphertexts, sorting, performance, and security against quantum computers. The article explains that FHE can support operations on encrypted data without exposing the underlying plaintext, while computational overhead remains a key limitation. ### Source excerpt I work on homomorphic encryption (HE or FHE for "fully" homomorphic encryption) and I have written a lot about it on this blog (see the relevant tag). This article is a collection of short answers to questions I see on various threads and news aggregators discussing FHE. Facts If a service uses FHE and can respond to encrypted queries, can't the service see your query? How is it possible to operate on encrypted data without seeing it? ## ESP-SparkBot：Large Language Model Robot with ESP32-S3 DevFeed: [ESP-SparkBot：Large Language Model Robot with ESP32-S3]() Original publisher: [Read original article]() Author: John Lee Published: 2025-04-23T00:00:00Z Content type: article Language: en Sources: [Blog on Developer Portal]() Topics: [ESP32-S3](), [Hardware](), [Artificial Intelligence](), [Language models](), [software-development]() Tags: [artificial-intelligence](), [blog](), [debugging](), [esp-now](), [esp32-s3](), [face-recognition](), [facial-recognition](), [hardware](), [home-automation](), [language-models](), [motion-detection](), [offline-speech-recognition](), [usb-screen-mirror](), [video]() ### AI overview This article introduces ESP-SparkBot, a low-cost, multifunctional AI robot built with ESP32-S3. It describes the robot's voice interaction, facial recognition, remote control, motion detection, multimedia capabilities, hardware design, power options, and supporting software framework. ### Source excerpt This article provides an overview of the ESP-SparkBot, its features, and functionality.It also details the hardware design and outlines the software framework that supports its operation. Introduction# With the booming development of generative artificial intelligence, large language models (LLMs) are becoming a core technology in the AI field. ## Building a Facial Recognition System with Qdrant DevFeed: [Building a Facial Recognition System with Qdrant]() Original publisher: [Read original article]() Author: info@qdrant.tech (Andrey Vasnetsov) Published: 2024-12-03T08:00:00Z Content type: tutorial Language: en Sources: [Qdrant Blog on Qdrant - Vector Search Engine]() Topics: [Facial recognition](), [Qdrant](), [Embeddings](), [AI search](), [Data pipelines](), [Streamlit](), [Machine learning](), [Front end]() Tags: [approximate-nearest-neighbor-search](), [bert](), [data](), [data-pipelines](), [developers](), [embeddings](), [facial-recognition](), [fasttext](), [hnsw](), [image-search](), [knn-algorithm](), [matching](), [neural-network](), [project](), [qdrant](), [recommender-system](), [saas](), [simaes-networks](), [similarity](), [technology](), [transformer](), [vector-search](), [vector-search-engine](), [vectors](), [word2vec]() ### AI overview A practical overview of building the Twin Celebrity facial-recognition app. It explains how FaceNet embeddings, Qdrant vector similarity search, ZenML data pipelines, and Streamlit work together to match a user's selfie with a celebrity look-alike. ### Source excerpt The Twin Celebrity App In the era of personalization, combining cutting-edge technology with fun can create engaging applications that resonate with users. One such project is the Twin Celebrity app, a tool that matches users with their celebrity look-alikes using facial recognition embeddings and vector search powered by Qdrant. This blog post dives into the architecture, tools, and practical advice for developers who want to build this app--or something similar. The Twin Celebrity app identifies which celebrity a user resembles by analyzing a selfie. The app utilizes: ## App lock via Face ID or biometrics DevFeed: [App lock via Face ID or biometrics]() Original publisher: [Read original article]() Author: Allison Published: 2024-08-06T22:08:01Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [Security](), [GitHub]() Tags: [app](), [biometrics](), [facial-recognition](), [fingerprint](), [github](), [github-mobile](), [mobile](), [security](), [security-feature]() ### AI overview GitHub Mobile adds an app lock using biometric authentication, such as fingerprint or facial recognition, to restrict access to the account on a mobile device and protect projects and data. The excerpt provides no setup details or platform-specific requirements. ### Source excerpt We're excited to introduce a new security feature in GitHub Mobile: app lock via biometrics. This adds an extra layer of security, ensuring only you can access your GitHub account... ## Passkeys: Authentication, Security, and Product Adoption DevFeed: [Passkeys: Authentication, Security, and Product Adoption]() Original publisher: [Read original article]() Author: FusionAuth Published: 2024-03-20T00:00:00Z Content type: article Language: en Sources: [FusionAuth]() Topics: [Passkeys](), [Authentication](), [Security](), [Digital Security](), [passwords](), [private key](), [Facial recognition]() Tags: [adoption](), [authentication](), [digital-security](), [education](), [facial-recognition](), [passkeys](), [passwords](), [private-key](), [security]() ### AI overview This promotional article explains passkeys as an authentication method that can replace or augment passwords. It describes their security model, biometric access options, cross-device user experience, and potential to reduce login friction and support product adoption. ### Source excerpt Join us for a free webinar to learn about passkeys, how they work, and how they can help set your business apart. ## Beyond Passwords - The Evolution of Digital Identity DevFeed: [Beyond Passwords - The Evolution of Digital Identity]() Original publisher: [Read original article]() Author: Brad McCarty Published: 2024-02-16T00:00:00Z Content type: article Language: en Sources: [FusionAuth]() Topics: [MFA](), [passwords](), [Authentication](), [Security](), [Single sign-on (SSO)](), [Facial recognition]() Tags: [authentication](), [education](), [facial-recognition](), [identity](), [mfa](), [passwords](), [security](), [sso]() ### AI overview An overview of digital identity's shift from password-based access toward multi-factor authentication, biometrics, and single sign-on. It explains how these approaches aim to improve security while reducing user friction. ### Source excerpt Our defenses are not just smarter, but also more intuitive, molding around our individual lives like never before. ## Launch Week 5 Hackathon Winners DevFeed: [Launch Week 5 Hackathon Winners]() Original publisher: [Read original article]() Author: Tyler Shukert Published: 2022-08-25T07:00:00Z Content type: news Language: en Sources: [Supabase]() Topics: [Supabase](), [Hackathon](), [Cache](), [React](), [User Interfaces](), [Security](), [Facial recognition](), [stripe](), [Flutter](), [App]() Tags: [caching](), [facial-recognition](), [flutter](), [open-source](), [react](), [security](), [stripe](), [ui]() ### AI overview Supabase announces the winners of its Launch Week 5 Hackathon, which received 46 submissions. The winning projects include a Supabase caching utility library, a React UI component library, a job board app, a notes and links app, a security desktop app, a Stripe data synchronization tool, a facial-recognition game, a quiz app, and a video journaling app. ### Source excerpt Announcing the winners of the Launch Week 5 Hackathon! ## Encryption & Privacy Policy and Technology DevFeed: [Encryption & Privacy Policy and Technology]() Original publisher: [Read original article]() Author: Adam Published: 2019-12-11T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Encryption](), [Facial recognition](), [Cryptography](), [recommendation systems]() Tags: [encryption](), [facial-recognition](), [privacy](), [recommendations](), [research]() ### AI overview A commentary roundup discusses an open letter arguing that weak encryption puts internet users at risk, nominations for the Caspar Bowden Award for privacy-enhancing technology research, and proposed rules for facial recognition technology at the Port of Seattle. ### Source excerpt A few tidbits in recent news. ## Web Authentication (WebAuthn) security keys DevFeed: [Web Authentication (WebAuthn) security keys]() Original publisher: [Read original article]() Author: Janey Annis Published: 2019-09-12T16:53:57Z Content type: release Language: en Sources: [GitHub Changelog]() Topics: [WebAuthn](), [Authentication]() Tags: [2019](), [android](), [android-phones](), [apple](), [authentication](), [brave](), [browsers](), [chrome](), [external](), [facial-recognition](), [github](), [hardware](), [ios](), [key](), [keys](), [security](), [security-keys](), [standard](), [support](), [webauthn]() ### AI overview GitHub supports WebAuthn authentication with external hardware security keys, Android phones, Chrome with TouchID, iOS Brave with a Yubico 5Ci key, and Windows Hello facial recognition or PIN. The excerpt says existing U2F hardware security keys need no additional action. It also notes browser availability varies, with Apple support expected in Fall 2019. ### Source excerpt GitHub now supports the WebAuthn standard for authentication. A broad array of security keys can be used across most major browsers (Apple will add support in Fall 2019). The following... ## Eigenfaces, for Facial Recognition DevFeed: [Eigenfaces, for Facial Recognition]() Original publisher: [Read original article]() Published: 2011-07-27T18:41:01Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Facial recognition](), [Algorithms]() Tags: [algorithm](), [covariance](), [eigenfaces](), [facial-recognition](), [images](), [inner-product](), [linear-algebra](), [mathematics](), [pixel](), [programming](), [vector]() ### AI overview This tutorial introduces eigenfaces for facial recognition. It outlines collecting sample face images, training a recognition algorithm, and classifying new images, then explains how grayscale images can be represented as matrices and vectors in a high-dimensional face space. ### Source excerpt This post assumes familiarity with the terminology and notation of linear algebra, particularly inner product spaces. Fortunately, we have both a beginner's primer on linear algebra and a follow-up primer on inner products. The Quest We are on a quest to write a program which recognizes images of faces. The general algorithm should be as follows. Get a bunch of sample images of people we want to recognize. Train our recognition algorithm on those samples.