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dc.contributor.authorUzun, Erkam
dc.date.accessioned2018-05-08T23:43:38Z
dc.date.available2018-05-08T23:43:38Z
dc.date.issued2018-04-12
dc.identifier.urihttp://hdl.handle.net/1853/59661
dc.descriptionPresented as part of Cybersecurity Demo Day on April 12, 2018 at 4:00 p.m. in the Krone Engineered Biosystems Building, Room 1005.en_US
dc.descriptionErkam Uzun is a third year Computer Science PhD student working in the Institute for Information Security and Privacy at Georgia Tech under the supervision of Prof. Wenke Lee. Before joining to Georgia Tech, he worked in Center for Cyber Security at New York University Abu Dhabi as a Research Engineer for two years. His research interests span a broad range of topics focusing largely on audio/visual authentication systems, security and privacy, digital audio and image forensics, multimedia computing, machine learning and optimization.en_US
dc.descriptionRuntime: 13:13 minutesen_US
dc.description.abstractMore organizations are turning to facial and voice recognition, or other biometric identifiers, to authenticate users and grant access to their systems. In particular, some services (e.g. Mastercard Identity Check) allow users to authenticate themselves by simply showing their face in front of their phone's camera, or simply speaking into the phone. Unfortunately, it's been shown that this can be easily forged in real time to defeat such authentication systems. This project introduces "Real Time Captcha (rtCaptcha)," a new, practical approach that places a formidable computation burden before adversaries by leveraging the proven security infrastructure of CAPTCHAs. In particular, rtCaptcha authenticates a user by taking a live video/audio recording of the user whiel also solving a CAPTCHA challenge question. This is in sharp contrast to simpler detection systems that only ask the user to blink, smile, or nod. Our user study showed that -- thanks to the humans' speed of solving random CAPTCHA challenges -- adversaries will have to appear and sound like the intended victim and solve the same challenge in less than 2 seconds in order to trick an authentication system. This is not possible by today's best machine-based or human attackers.en_US
dc.format.extent13:13 minutes
dc.language.isoen_USen_US
dc.publisherGeorgia Institute of Technologyen_US
dc.relation.ispartofseriesCybersecurity Demo Day 2018en_US
dc.subjectAuthenticationen_US
dc.subjectLiveness detectionen_US
dc.titlertCaptchaen_US
dc.typeLectureen_US
dc.typeVideoen_US
dc.contributor.corporatenameGeorgia Institute of Technology. Institute for Information Security & Privacyen_US
dc.contributor.corporatenameGeorgia Institute of Technology. School of Computer Scienceen_US


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