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Open Access Knowledge and Scholarship

Date of Award


Culminating Project Type




Degree Name

Computer Science: M.S.


Computer Science and Information Technology


School of Science and Engineering

First Advisor

Alanka Mailewa

Second Advisor

Dale Buske

Third Advisor

Mark Schmidt

Fourth Advisor

Aleksander Tomovic

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Keywords and Subject Headings

Blind Bidding Auction, Fully Homomorphic Encryption, FHE


In blind-bidding auctions, determining the winner requires processing bids without revealing non-winning bid information. This study explores the use of Fully Homomorphic Encryption (FHE) as a solution for this challenge. FHE permits operations like addition and multiplication on encrypted data, enabling potentially arbitrary computations without exposing underlying values. However, leveraging FHE for blind-bidding auctions is not straightforward. Classic sorting algorithms are not directly applicable due to FHE’s constraints. This thesis presents our approach to designing a blind-bidding auction using FHE, focusing specifically on determining the maximum bid within the given computational boundaries.

Available for download on Friday, November 15, 2024