Entries Tagged "identification"

Page 11 of 27

Dance Moves As an Identifier

A burglar was identified by his dance moves, captured on security cameras:

“The 16-year-old juvenile suspect is known for his ‘swag,’ or signature dance move,” Heyse said, “and [he] does it in the hallways at school.” Presumably, although the report doesn’t make it clear, a classmate or teacher saw the video, recognized the distinctive swag and notified authorities.

But is swag admissible to identify a defendant? Assuming it really is unique or distinctive—and it looks that way from the clip, but I’m no swag expert—I’d say yes.

Posted on April 19, 2012 at 1:03 PM • View Comments

Authentication by "Cognitive Footprint"

DARPA is funding research into new forms of biometrics that authenticate people as they use their computer: things like keystroke patterns, eye movements, mouse behavior, reading speed, and surfing and e-mail response behavior. The idea—and I think this is a good one—is that the computer can continuously authenticate people, and not just authenticate them once when they first start using their computers.

I remember reading a science fiction story about a computer worm that searched for people this way: going from computer to computer, trying to identify a specific individual.

Posted on January 23, 2012 at 11:49 AM • View Comments

Butt Identification

Here’s a new biometric: how you sit:

…researchers there developed a system that can recognize a person by the backside when the person takes a seat. The system performs a precise measurement of the person’s posterior, its contours and the way the person applies pressure on the seat. The developers say that in lab tests, the system was able to recognize people with 98 percent accuracy.

Posted on December 28, 2011 at 11:40 AM • View Comments

Identifying Speakers in Encrypted Voice Communication

I’ve already written how it is possible to detect words and phrases in encrypted VoIP calls. Turns out it’s possible to detect speakers as well:

Abstract: Most of the voice over IP (VoIP) traffic is encrypted prior to its transmission over the Internet. This makes the identity tracing of perpetrators during forensic investigations a challenging task since conventional speaker recognition techniques are limited to unencrypted speech communications. In this paper, we propose techniques for speaker identification and verification from encrypted VoIP conversations. Our experimental results show that the proposed techniques can correctly identify the actual speaker for 70-75% of the time among a group of 10 potential suspects. We also achieve more than 10 fold improvement over random guessing in identifying a perpetrator in a group of 20 potential suspects. An equal error rate of 17% in case of speaker verification on the CSLU speaker recognition corpus is achieved.

Posted on September 16, 2011 at 12:31 PM • View Comments

The Effects of Social Media on Undercover Policing

Social networking sites make it very difficult, if not impossible, to have undercover police officers:

“The results found that 90 per cent of female officers were using social media compared with 81 per cent of males.”

The most popular site was Facebook, followed by Twitter. Forty seven per cent of those surveyed used social networking sites daily while another 24 per cent used them weekly. All respondents aged 26 years or younger had uploaded photos of themselves onto the internet.

“The thinking we had with this result means that the 16-year-olds of today who might become officers in the future have already been exposed.

“It’s too late [for them to take it down] because once it’s uploaded, it’s there forever.”

There’s another side to this issue as well. Social networking sites can help undercover officers with their backstory, by building a fictional history. Some of this might require help from the company that owns the social networking site, but that seems like a reasonable request by the police.

I am in the middle of reading Diego Gambetta’s book Codes of the Underworld: How Criminals Communicate. He talks about the lengthy vetting process organized crime uses to vet new members—often relying on people who knew the person since birth, or people who served time with him in jail—to protect against police informants. I agree that social networking sites can make undercover work even harder, but it’s gotten pretty hard even without that.

Posted on August 31, 2011 at 6:21 AM • View Comments

Identifying People by their Writing Style

The article is in the context of the big Facebook lawsuit, but the part about identifying people by their writing style is interesting:

Recently, a team of computer scientists at Concordia University in Montreal took advantage of an unusual set of data to test another method of determining e-mail authorship. In 2003, the Federal Energy Regulatory Commission, as part of its investigation into Enron, released into the public domain hundreds of thousands of employee e-mails, which have become an important resource for forensic research. (Unlike novels, newspapers or blogs, e-mails are a private form of communication and aren’t usually available as a sizable corpus for analysis.)

Using this data, Benjamin C. M. Fung, who specializes in data mining, and Mourad Debbabi, a cyber-forensics expert, collaborated on a program that can look at an anonymous e-mail message and predict who wrote it out of a pool of known authors, with an accuracy of 80 to 90 percent. (Ms. Chaski claims 95 percent accuracy with her syntactic method.) The team identifies bundles of linguistic features, hundreds in all. They catalog everything from the position of greetings and farewells in e-mails to the preference of a writer for using symbols (say, “$” or “%”) or words (“dollars” or “percent”). Combining all of those features, they contend, allows them to determine what they call a person’s “write-print.”

It seems reasonable that we have a linguistic fingerprint, although 1) there are far fewer of them than finger fingerprints, 2) they’re easier to fake. It’s probably not much of a stretch to take that software that “identifies bundles of linguistic features, hundreds in all” and use the data to automatically modify my writing to look like someone else’s.

EDITED TO ADD (8/3): A good criticism of the science behind author recognition, and a paper on how to evade these systems.

Posted on August 3, 2011 at 6:08 AM • View Comments

Developments in Facial Recognition

Eventually, it will work. You’ll be able to wear a camera that will automatically recognize someone walking towards you, and a earpiece that will relay who that person is and maybe something about him. None of the technologies required to make this work are hard; it’s just a matter of getting the error rate down low enough for it to be a useful system. And there have been a number of recent research results and news stories that illustrate what this new world might look like.

The police want this sort of system. I already blogged about MORIS, an iris-scanning technology that several police forces in the U.S. are using. The next step is the face-scanning glasses that the Brazilian police claim they will be wearing at the 2014 World Cup.

A small camera fitted to the glasses can capture 400 facial images per second and send them to a central computer database storing up to 13 million faces.

The system can compare biometric data at 46,000 points on a face and will immediately signal any matches to known criminals or people wanted by police.

In the future, this sort of thing won’t be limited to the police. Facebook has recently embarked on a major photo tagging project, and already has the largest collection of identified photographs in the world outside of a government. Researchers at Carnegie Mellon University have combined the public part of that database with a camera and face-recognition software to identify students on campus. (The paper fully describing their work is under review and not online yet, but slides describing the results can be found here.)

Of course, there are false positives—as there are with any system like this. That’s not a big deal if the application is a billboard with face-recognition serving different ads depending on the gender and age—and eventually the identity—of the person looking at it, but is more problematic if the application is a legal one.

In Boston, someone erroneously had his driver’s licence revoked:

It turned out Gass was flagged because he looks like another driver, not because his image was being used to create a fake identity. His driving privileges were returned but, he alleges in a lawsuit, only after 10 days of bureaucratic wrangling to prove he is who he says he is.

And apparently, he has company. Last year, the facial recognition system picked out more than 1,000 cases that resulted in State Police investigations, officials say. And some of those people are guilty of nothing more than looking like someone else. Not all go through the long process that Gass says he endured, but each must visit the Registry with proof of their identity.

[…]

At least 34 states are using such systems. They help authorities verify a person’s claimed identity and track down people who have multiple licenses under different aliases, such as underage people wanting to buy alcohol, people with previous license suspensions, and people with criminal records trying to evade the law.

The problem is less with the system, and more with the guilty-until-proven-innocent way in which the system is used.

Kaprielian said the Registry gives drivers enough time to respond to the suspension letters and that it is the individual’s “burden’” to clear up any confusion. She added that protecting the public far outweighs any inconvenience Gass or anyone else might experience.

“A driver’s license is not a matter of civil rights. It’s not a right. It’s a privilege,” she said. “Yes, it is an inconvenience [to have to clear your name], but lots of people have their identities stolen, and that’s an inconvenience, too.”

IEEE Spectrum and The Economist have published similar articles.

EDITED TO ADD (8/3): Here’s a system embedded in a pair of glasses that automatically analyzes and relays micro-facial expressions. The goal is to help autistic people who have trouble reading emotions, but you could easily imagine this sort of thing becoming common. And what happens when we start relying on these computerized systems and ignoring our own intuition?

EDITED TO ADD: CV Dazzle is camouflage from face detection.

Posted on August 2, 2011 at 1:33 PM • View Comments

1 … 9 10 11 12 13 … 27

Sidebar photo of Bruce Schneier by Joe MacInnis.