Lecturer Candidate: Fattaneh Bayatbabolghani
Dreese Labs 480
2015 Neil Avenue, Columbus, Ohio 43210
Secure Biometric Computation and Outsourcing
Biometric computations are becoming increasingly popular, and their impact in real world applications is undeniable. There are different types of biometric data used in a variety of applications such as biometric recognition including verification and identification. Because of the highly sensitive nature of biometric data, its protection is essential during biometric computations.
Based on the computations that need to be carried out and the type of biometric data, there is a need for application-specific privacy preserving solutions. These solutions can be provided by developing secure biometric computations in a way that no information gets revealed during the protocol execution. In some biometric applications (e.g. verification and identification), data is distributed amongst different parties engaged in computations. In some other applications, the execution of computations is bounded by the computational power of the parties, motivating the use of cloud or external servers. In both these cases, 1) there is a higher risk for sensitive data to be disclosed, making secure biometric protocols a prominent need for such practical applications, 2) it is more challenging to develop novel and efficient solutions for these computational settings, making the design of secure biometric protocols a research-worthy effort.
In this talk, Fattaneh focuses on three different biometric modalities (Voice, DNA, Fingerprint) which require various computational settings. The proposed solutions consider the nature of computational setting (two-party and multi-party settings) of biometric applications in practice and efficiently protect the data during the computations. In addition, the secure protocols and building blocks which will be presented are general and can be used for other applications where the same data types and settings are used.
Bio: Fattaneh Bayatbabolghani is a recent Ph.D. graduate from Department of Computer Science and Engineering at University of Notre Dame. Her primary research interest is designing general and efficient privacy-preserving solutions motivated by real-world applications. During her Ph.D., she has been designing novel, general, and efficient privacy-preserving solutions and protocols which can be used for different applications, but are specifically used for biometric computations.
Bio: Fattaneh Bayatbabolghani is a recent Ph.D. graduate from Department of Computer Science and Engineering at University of Notre Dame. Her primary research interest is designing general and ecient privacy-preserving solutions motivated by real-world applications. During her Ph.D., she has been designing novel, general, and ecient privacy-preserving solutions and protocols which can be used for di erent applications, but are speci cally used for biometric computations.
Host: Rafe Wenger