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Asymmetric commutative encryption scheme based efficient solution to the millionaires' problem

conference contribution
posted on 2018-01-01, 00:00 authored by M Liu, P Nanda, X Zhang, C Yang, Shui Yu, Jianxin LiJianxin Li
© 2018 IEEE. Secure multiparty computation (SMC) is an important scheme in cryptography and can be applied in various real-life problems. The first SMC problem is the millionaires' problem which involves two-party secure computation. Because the efficiency of public key encryption scheme appears less than symmetric encryption scheme, most existing solutions based on public key cryptography to this problem is inefficient. Thus, a solution based on the symmetric encryption scheme has been proposed. Although it is claimed that this approach can be efficient and practical, we discover that there exist several severe security flaws in this solution. In this paper, we analyze the vulnerability of existing solutions, and propose a new scheme based on the Decisional Diffie-Hellman hypothesis (DDH). Our solution also uses two special encodings (0-encoding and 1-encoding) generated by our modified encoding method to reduce the computation cost of modular multiplications. Extensive experiments are conducted to evaluate the efficiency of our solution, and the experimental results show that our solution can be much more efficient and be approximately 8000 times faster than the solution based on symmetric encryption scheme for a 32-bit input and short-term security. Moreover, our solution is also more efficient than the state-of-the-art solution.

History

Event

Trust, Security And Privacy In Computing And Communications & Big Data Science And Engineering. Combined Conference (2018 : 17th & 12th : New York, New York)

Pagination

990 - 995

Publisher

IEEE

Location

New York, New York

Place of publication

Piscataway, N.J.

Start date

2018-08-01

End date

2018-08-03

ISBN-13

9781538643877

Language

eng

Publication classification

E1 Full written paper - refereed

Title of proceedings

IEEE TrustCom & BigDataSE 2018 : Proceedings of the 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering Combined Conference