Oregon State University

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MS Final Examination – Gungor Basa


Friday, December 2, 2016 9:00 AM - 11:00 AM

Image Based Crypto
Ability to create reproducible cryptographically secure keys from temporal environments have potential to be a major contributor to effective cryptographic mechanisms. Due to noisy nature of these environments, achieving this goal in a user friendly fashion is very challenging task. Especially, there exists a research gap to create reproducible keys from image data.

In this thesis, towards addressing aforementioned challenge, we developed a new image based reproducible key derivation mechanism, which leverages deep learning techniques alongside with fuzzy extractor schemes to enable reproducible symmetric key creation from temporal visual environments. Our technique uses deep learning and fuzzy extractors as fundamental building blocks. Deep learning harnesses patterns in images to minimize the noise, and permit successful utilization of fuzzy extractor schemes to handle errors. Using these techniques together enables reproducible key generation.

Major Advisor:  Attila Yavuz
Committee: Mike Rosulek
Committee: Fuxin Li
GCR: Maggie Niess


Kelley Engineering Center (campus map)
3114
Nicole Thompson
1 541 737 3617
NicoleThompson at oregonstate.edu
Sch Elect Engr/Comp Sci
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