PhD Proposal by Erkam Uzun

Event Details
  • Date/Time:
    • Friday January 29, 2021 - Saturday January 30, 2021
      12:00 pm - 1:59 pm
  • Location: Atlanta, GA
  • Phone:
  • URL: Bluejeans
  • Email:
  • Fee(s):
  • Extras:
No contact information submitted.

Summary Sentence: Security and Privacy in Biometrics-Based Systems

Full Summary: No summary paragraph submitted.

Title: Security and Privacy in Biometrics-Based Systems


Erkam Uzun

Ph.D. Student in Computer Science

School of Computer Science

College of Computing

Georgia Institute of Technology


Date: January 28, 2021

Time: 12:00 PM to 02:00 PM (EST)

Location (remote via Bluejeans):



Dr. Wenke Lee (Advisor, School of Computer Science, Georgia Institute of Technology)

Dr. Mustaque Ahamad (School of Computer Science, Georgia Institute of Technology)

Dr. Irfan Essa (School of Interactive Computing, Georgia Institute of Technology)

Dr. Alexandra Boldyreva (School of Computer Science, Georgia Institute of Technology)

Dr. Vladimir Kolesnikov (School of Computer Science, Georgia Institute of Technology)



Advancement in deep learning (DL) based biometric identification and the proliferation of affordable sensors made biometrics pivotal players in authentication and surveillance systems. On the one hand, major companies (e.g., MasterCard, AliPay) already adopted facial/voice-based authentication as part of their security measures. On the other hand, governments and private sectors use biometric recognition for a broader impact, such as identifying and catching “person of interest”, or targeted advertisement. While these technologies could have enormous impacts, existing biometric authentication and surveillance systems are vulnerable to several kinds of attacks and jeopardize the privacy of people's sensitive data. In this proposal, I aim to provide solutions to these challenges. First, I will present vulnerabilities against impersonation attacks in an authentication setting. Our study shows that many cloud-based audio/visual recognition systems (e.g., Amazon Rekognition) can be defeated by the crudest impersonations. Then, I will briefly present our live biometric verification system, the Real Time Captcha (rtCaptcha), a practical approach that places a formidable computational burden on the attacker by combining dynamic, live detection with a randomized Captcha challenge for stronger security. Then, I will present our privacy-preserving remote biometric authentication system, Justitia, which makes DL-inferences of biometric data compatible with the standard privacy-preserving primitives, like fuzzy extractors. Justitia lets a remote server to authenticate a client without receiving his/her biometric data in the process of enrollment and authentication. In the end, I will briefly discuss my ongoing research that uses secure multi-party computation techniques for a privacy-preserving biometric search.



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482 795 225


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Additional Information

In Campus Calendar

Graduate Studies

Invited Audience
Faculty/Staff, Public, Graduate students, Undergraduate students
Phd proposal
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: Jan 22, 2021 - 11:53am
  • Last Updated: Jan 22, 2021 - 11:53am