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In what might be described as a real-life Black Mirror episode, a Harvard student uses facial recognition with Meta Ray-Ban 2 smart sunglasses - to dig up personal data on every face he sees in real time. AnhPhu Nguyen, a junior at Harvard University, uses the livestreaming feature of his Meta Ray-Ban 2 smart glasses while a connected computer monitors the feed in real-time. He employs publicly available AI-powered facial recognition software to detect faces and scour the internet for more images of those individuals. He then uses databases like voter registration and online articles to gather names, addresses, phone numbers, next of kin, and even social security numbers. All of this data is scraped together using an LLM (Large Language Model) similar to ChatGPT which aggregates the data into a searchable profile that's fed straight back to his phone. This entire process takes only seconds from being captured discreetly via the glasses to being displayed on his phone Are you surprised that someone has come up with this? I am not. See more news like this at https://lnkd.in/eHszY5qH #AI #metaverse #dataprotection #databreach #cyber

A new AI model can mask a personal image without destroying its quality, which will help to protect your privacy. Artificial intelligence (AI) could hold the key to hiding your personal photos from unwanted facial recognition software and fraudsters, all without destroying the image quality. A new study from Georgia Tech university, details how researchers created an AI model called "Chameleon," which can produce a digital "single, personalized privacy protection (P-3) mask" for personal photos that thwarts unwanted facial scanning from detecting a person's face. Chameleon will instead cause facial recognition scanners to recognize the photos as being someone else. The researchers would also like to apply Chameleon’s obfuscation methods beyond the protection of individual users’ personal images. "We would like to use these techniques to protect images from being used to train artificial intelligence generative models. We could protect the image information from being used without consent,” said Georgia Tech doctoral student Tiansheng Huang, who was also involved in the development of Chameleon... Source: https://lnkd.in/eF-sXpSB #artificialintelligence #privacy #deepfakes #facialrecognition #cybersecurity

AI can be used for protection…very cool 

Reflections on Avishkar 2024: Presenting the Anti-AI System Concept. Participating in Avishkar 2024 was a defining experience in my academic journey, especially as my concept for an "Anti-AI System" achieved 2nd rank at the undergraduate level. Presenting this idea allowed me to explore the pressing need for responsible AI usage, especially in fields where unchecked AI might have unintended consequences. The Anti-AI System I proposed aims to establish safeguards that monitor and manage potentially harmful AI actions, creating a framework where human oversight is central to AI operations. During the Q&A, the conversations sparked were thought-provoking and highlighted critical aspects—like the ethical considerations, cybersecurity applications, and the technical feasibility of such a system. The judges and audience's interest in these points validated the relevance of this concept in today’s AI landscape.

Meet 'Chameleon' – an AI model that can protect you from facial recognition thanks to a sophisticated digital mask. A new AI model can mask a personal image without destroying its quality, which will help to protect your privacy. #ai #personalimage #personalid https://flip.it/tmZ4Vm

We are thrilled to announce the publication of our latest journal, "The Missing Link in Network Intrusion Detection: Taking AI/ML Research Efforts to Users." in IEEE Access. This article was written by Katharina Dietz, Michael Mühlhauser, Jochen Kögel, Stephan Schwinger, Marleen Sichermann, Michael Seufert, Dominik Herrmann, Tobias Hoßfeld. 🔍 What is it about Intrusion Detection Systems (IDS) face the growing complexity of detecting network attacks quickly, with AI and ML gaining research traction but struggling with real-world adoption due to issues like explainability and usability. Our user-centric literature survey, utilizing personas, identifies barriers, and offers guidelines to enhance the practical adoption of AI/ML research results in IDS, addressing data appropriateness, reproducibility, explainability, practicability, usability, and privacy. 📘 *You can read the full article and our findings here:* https://lnkd.in/dBkJYu43

AI for good happening here with Simprints

In a recent interview with Betanews, Inc., I had the opportunity to share insights on the ethical issue of bias in biometrics and what needs to be done to prevent it. We discussed important questions, including: ▪️ In recent months, there's been extensive coverage of facial recognition systems being biased and inherently flawed. Do you think this is a fair assessment of the technology as a whole? ▪️ Are there differences in the way various facial recognition systems work? Are some more or less prone to errors? ▪️ What needs to happen in order to make these systems more universally accurate? ▪️ What are some guidelines organizations should consider as they evaluate the implementation of facial recognition systems? See my answers for each in the full article: https://lnkd.in/eF7Mt8Rk #Biometrics #Bias #AI #Technology

➡ Regulation of AI in Biometrics The use of biometric technology and AI, from fingerprint scanners to facial recognition, has become increasingly widespread, offering a range of benefits such as convenience, faster service, and improved security. As technology advances, so will the forms of biometric data that can be derived from individuals. Data relating to the physical or psychological characteristics of an individual have been around for several years, but data relating to behavioural characteristics are novel. This raises significant concerns about privacy, equity, and discrimination. Learn more: https://lnkd.in/dDQnsehn #AI #Biometrics #AIRegulation #ResponsibleAI

NEW: In a recent interview with Betanews, Inc., Aware CTO, Dr. Mohamed Lazzouni had the opportunity to share insights on the ethical issue of bias in biometrics and what needs to be done to prevent it. He covered important questions, including: ▪️ In recent months, there's been extensive coverage of facial recognition systems being biased and inherently flawed. Do you think this is a fair assessment of the technology as a whole? ▪️ Are there differences in the way various facial recognition systems work? Are some more or less prone to errors? ▪️ What needs to happen in order to make these systems more universally accurate? ▪️ What are some guidelines organizations should consider as they evaluate the implementation of facial recognition systems? Check out his answers for each in the full article: https://lnkd.in/gPDEK4JX #Biometrics #Bias #AI #Technology