Entries Tagged "biometrics"

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Microbe Biometric

Interesting:

Franzosa and colleagues used publicly available microbiome data produced through the Human Microbiome Project (HMP), which surveyed microbes in the stool, saliva, skin, and other body sites from up to 242 individuals over a months-long period. The authors adapted a classical computer science algorithm to combine stable and distinguishing sequence features from individuals’ initial microbiome samples into individual-specific “codes.” They then compared the codes to microbiome samples collected from the same individuals’ at follow-up visits and to samples from independent groups of individuals.

The results showed that the codes were unique among hundreds of individuals, and that a large fraction of individuals’ microbial “fingerprints” remained stable over a one-year sampling period. The codes constructed from gut samples were particularly stable, with more than 80% of individuals identifiable up to a year after the sampling period.

Posted on May 15, 2015 at 6:20 AMView Comments

Identifying When Someone Is Operating a Computer Remotely

Here’s an interesting technique to detect Remote Access Trojans, or RATS: differences in how local and remote users use the keyboard and mouse:

By using biometric analysis tools, we are able to analyze cognitive traits such as hand-eye coordination, usage preferences, as well as device interaction patterns to identify a delay or latency often associated with remote access attacks. Simply put, a RAT’s keyboard typing or cursor movement will often cause delayed visual feedback which in turn results in delayed response time; the data is simply not as fluent as would be expected from standard human behavior data.

No data on false positives vs. false negatives, but interesting nonetheless.

Posted on March 9, 2015 at 1:03 PMView Comments

Fidgeting as Lie Detection

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) that are coded or rated by humans. The results are characterized by inconsistent and often contradictory findings, with small-stakes lies under lab conditions detected at rates only slightly better than guessing. Building on previous work that uses automatic analysis of facial videos and rhythmic body movements to diagnose stress, we set out to see whether a full body motion capture suit, which records the position, velocity and orientation of 23 points in the subject’s body, could yield a better signal of deception. Interviewees of South Asian (n = 60) or White British culture (n = 30) were required to either tell the truth or lie about two experienced tasks while being interviewed by somebody from their own (n = 60) or different culture (n = 30). We discovered that full body motion — the sum of joint displacements — was indicative of lying approximately 75% of the time. Furthermore, movement was guilt-related, and occurred independently of anxiety, cognitive load and cultural background. Further analyses indicate that including individual limb data in our full bodymotion measurements, in combination with appropriate questioning strategies, can increase its discriminatory power to around 82%. This culture-sensitive study provides an objective and inclusive view on how people actually behave when lying. It appears that full body motion can be a robust nonverbal indicator of deceit, and suggests that lying does not cause people to freeze. However, should full body motion capture become a routine investigative technique, liars might freeze in order not to give themselves away; but this in itself should be a telltale.

This is a first research study, and the results might not be robust. But it certainly is interesting.

Blog post. News article. Slashdot thread.

Posted on January 6, 2015 at 2:44 PMView Comments

People Are Not Very Good at Matching Photographs to People

We have an error rate of about 15%:

Professor Mike Burton, Sixth Century Chair in Psychology at the University of Aberdeen said: “Psychologists identified around a decade ago that in general people are not very good at matching a person to an image on a security document.

“Familiar faces trigger special processes in our brain — we would recognise a member of our family, a friend or a famous face within a crowd, in a multitude of guises, venues, angles or lighting conditions. But when it comes to identifying a stranger it’s another story.

“The question we asked was does this fundamental brain process that occurs have any real importance for situations such as controlling passport issuing ­ and we found that it does.”

The ability of Australian passport officers, for whom accurate face matching is central to their job and vital to border security, was tested in the latest study, which involved researchers from the Universities of Aberdeen, York and New South Wales Australia.

In one test, passport officers had to decide whether or not a photograph of an individual presented on their computer screen matched the face of a person standing in front of their desk.

It was found that on 15% of trials the officers decided that the photograph on their screen matched the face of the person standing in front of them, when in fact, the photograph showed an entirely different person.

Posted on August 25, 2014 at 7:08 AMView Comments

Automatic Scanning for Highly Stressed Individuals

This borders on ridiculous:

Chinese scientists are developing a mini-camera to scan crowds for highly stressed individuals, offering law-enforcement officers a potential tool to spot would-be suicide bombers.

[…]

“They all looked and behaved as ordinary people but their level of mental stress must have been extremely high before they launched their attacks. Our technology can detect such people, so law enforcement officers can take precautions and prevent these tragedies,” Chen said.

Officers looking through the device at a crowd would see a mental “stress bar” above each person’s head, and the suspects highlighted with a red face.

The researchers said they were able to use the technology to tell the difference between high-blood oxygen levels produced by stress rather than just physical exertion.

I’m not optimistic about this technology.

Posted on August 13, 2014 at 6:20 AMView Comments

Fingerprinting Computers By Making Them Draw Images

Here’s a new way to identify individual computers over the Internet. The page instructs the browser to draw an image. Because each computer draws the image slightly differently, this can be used to uniquely identify each computer. This is a big deal, because there’s no way to block this right now.

Article. Hacker News thread.

EDITED TO ADD (7/22): This technique was first described in 2012. And it seems that NoScript blocks this. Privacy Badger probably blocks it, too.

EDITED TO ADD (7/23): EFF has a good post on who is using this tracking system — the White House is — and how to defend against it.

And a good story on BoingBoing.

Posted on July 21, 2014 at 3:34 PMView Comments

Details of Apple's Fingerprint Recognition

This is interesting:

Touch ID takes a 88×88 500ppi scan of your finger and temporarily sends that data to a secure cache located near the RAM, after the data is vectorized and forwarded to the secure enclave located on the top left of the A7 near the M7 processor it is immediately discarded after processing. The fingerprint scanner uses subdermal ridge flows (inner layer of skin) to prevent loss of accuracy if you were to have micro cuts or debris on your finger.

With iOS 7.1.1 Apple now takes multiple scans of each position you place finger at setup instead of a single one and uses algorithms to predict potential errors that could arise in the future. Touch ID was supposed to gradually improve accuracy with every scan but the problem was if you didn’t scan well on setup it would ruin your experience until you re-setup your finger. iOS 7.1.1 not only removes that problem and increases accuracy but also greatly reduces the calculations your iPhone 5S had to make while unlocking the device which means you should get a much faster unlock time.

Posted on April 29, 2014 at 6:47 AMView Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.