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Georgia Tech reveals new voice authentication technology

Posted: 28 Oct 2010 ?? ?Print Version ?Bookmark and Share

Keywords:voice? phishing? security?

Researchers at Georgia Institute of Technology report that they have developed an authentication technology which can identify a digital fingerprint hidden within voice signals. This will be useful for revealing fraud and thwarting voice phishing scams.

When caller ID identifies a trusted caller such as a credit-card bank, it may be standard procedure to ask you to give your password for security purposes. Unfortunately, criminals can easily fake caller ID and use the same sort of phishing scams that are used on the Internet.

The voice authentication technology from Georgia Tech can be added onto any phone to positively identify the caller with 100 percent accuracy, according to Mustaque Ahamad, director, Georgia Tech Information Security Center (GTISC). He worked on the project with Patrick Traynor and Vijay Balasubramaniyan.

According to Balasubramaniyan, audio leaves telltale traces that reveal the order and type of each network that a voice call must traverse, from state-of-the-art VoIP to wireless cellular to legacy land lines.

While the technique cannot reveal a precise location or IP address, it can identify trusted callers with whom you have spoken several times before, and alert you when the caller's phone does not match what the caller ID says.

The system works independently of the telephone with which it is being used and requires no actions on the part of the carriers or the phone makers. Instead it just "listens for" the embedded signatures in the audio in order to trace what the researchers term a "call's provenance," its origin and routing method.

"Audio inherently embeds details of the networks it traverses. This is what allows us to determine the provenance of a call at the recipient's end," said Balasubramaniyan. "For example, when an audio packet is lost on the Internet, it stays lost, but it is not perceptible to the human ear."

Telephone calls are difficult to authenticate because they are repeatedly decoded and re-encoded each time pass through a network gateway.

By compiling these imperceptible audio cues, such as the sound of dropped packets, the researchers have crafted an algorithm called Pindrop, which learns the unique digital signature of every phone from which your receive calls. After just one phone call, Pindrop can identify the caller with 90 percent accuracy, according to Balasubramaniyan. After two calls its accuracy jumps to 96 percent and by the time a fifth call is made, the researchers say Pindrop has 100 percent accuracy at identifying the caller.

The researchers are also looking to expand Pindrop's capabilities, with built-in capabilities that identify the country of origin of a call even if you have never received a call from there before. So far they have gained experience in learning the difference between audio call signatures coming from connections to Australia, India, United Arab Emirates, United Kingdom and France.

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