Publication Date

12-2017

Date of Final Oral Examination (Defense)

10-19-2017

Type of Culminating Activity

Thesis

Degree Title

Master of Science in Computer Science

Department

Computer Science

Supervisory Committee Chair

Gaby Dagher, Ph.D.

Supervisory Committee Member

Dianxiang Xu, Ph.D.

Supervisory Committee Member

Marion Scheepers, Ph.D.

Abstract

Secure multiparty protocols are useful tools for parties wishing to jointly compute a function while keeping their input data secret. The millionaires’ problem is the first secure two-party computation problem, where the goal is to securely compare two private numbers without a trusted third-party. There have been several solutions to the problem, including Yao’s protocol [Yao, 1982] and Mix and Match [Jakobsson and Juels, 2000]. However, Yao’s Protocol is not secure in the malicious model and Mix and Match unnecessarily releases theoretically breakable encryptions of information about the data that is not needed for the comparison. In addition, neither protocol has any verification of the validity of the inputs before they are used. In this thesis, we introduce Variance, a privacy-preserving two-party protocol for solving the Yao’s millionaires’ problem in a Bitcoin setting, in which each party controls several Bitcoin accounts (public Bitcoin addresses) and they want to find out who owns more bitcoins without revealing (1) how many accounts they own and the balance of each account, (2) the addresses associated with their accounts, and (3) their total wealth of bitcoins while assuring the other party that they are not claiming more bitcoin than they possess. We utilize commitments, encryptions, zero knowledge proofs, and homomorphisms as the major computational tools to provide a solution to the problem, and subsequently prove that the solution is secure against active adversaries in the malicious model.

DOI

https://doi.org/10.18122/B2CD9K

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