Informations about SSL certificates and networks security
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There’s interesting research on using a set of “master” digital fingerprints to fool biometric readers. The work is theoretical at the moment, but they might be able to open about two-thirds of iPhones with these master prints. Definitely something to keep watching. Research paper (behind a paywall). Powered by WPeMatico
LyreBird is a system that can accurately reproduce the voice of someone, given a large amount of sample inputs. It’s pretty good — listen to the demo here — and will only get better over time. The applications for recorded-voice forgeries are obvious, but I think the larger security risk will be real-time forgery. Imagine … Read More “Forging Voice” »
Mike Specter has an interesting idea on how to make biometric access-control systems more secure: add a duress code. For example, you might configure your iPhone so that either thumb or forefinger unlocks the device, but your left middle finger disables the fingerprint mechanism (useful in the US where being compelled to divulge your password … Read More “Duress Codes for Fingerprint Access Control” »
There’s research in using a heartbeat as a biometric password. No details in the article. My guess is that there isn’t nearly enough entropy in the reproducible biometric, but I might be surprised. The article’s suggestion to use it as a password for health records seems especially problematic. “I’m sorry, but we can’t access the … Read More “Heartbeat as Biometric Password” »
This is some interesting research. You can fool facial recognition systems by wearing glasses printed with elements of other peoples’ faces. Mahmood Sharif, Sruti Bhagavatula, Lujo Bauer, and Michael K. Reiter, “Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition“: ABSTRACT: Machine learning is enabling a myriad innovations, including new algorithms for … Read More “Fooling Facial Recognition Systems” »
Neural networks are good at identifying faces, even if they’re blurry: In a paper released earlier this month, researchers at UT Austin and Cornell University demonstrate that faces and objects obscured by blurring, pixelation, and a recently-proposed privacy system called P3 can be successfully identified by a neural network trained on image datasets — in … Read More “Using Neural Networks to Identify Blurred Faces” »
Another paper on using Wi-Fi for surveillance. This one is on identifying people by their body shape. “FreeSense:Indoor Human Identification with WiFi Signals“: Abstract: Human identification plays an important role in human-computer interaction. There have been numerous methods proposed for human identification (e.g., face recognition, gait recognition, fingerprint identification, etc.). While these methods could be … Read More “Using Wi-Fi Signals to Identify People by Body Shape” »
Apple received a patent earlier this year on collecting biometric information of an unauthorized device user. The obvious application is taking a copy of the fingerprint and photo of someone using as stolen smartphone. Note that I have no opinion on whether this is a patentable idea or the patent is valid. Powered by WPeMatico
Sophie Van Der Zee and colleagues have a new paper on using body movement as a lie detector: Abstract: We present a new robust signal for detecting deception: full body motion. Previous work on detecting deception from body movement has relied either on human judges or on specific gestures (such as fidgeting or gaze aversion) … Read More “Fidgeting as Lie Detection” »