Privacy Preserving Computation in Home Loans Using the FRESCO Framework

Chan, Fook Mun and Xu, Quanqing and Seah, Hao Jian and Keoh, Sye Loong and Tang, Zhaohui and Aung, Khin Mi Mi (2019) Privacy Preserving Computation in Home Loans Using the FRESCO Framework. In: 2018 Future of Information and Communication Conference (FICC 2018), 5-6 April, 2018, Singapore, Singapore.


Abstract

Secure Multiparty Computation (SMC) is a subfield of cryptography that allows multiple parties to compute jointly on a function without revealing their inputs to others. The technology is able to solve potential privacy issues that arises when a trusted third party is involved, like a server. This paper aims to evaluate implementations of Secure Multiparty Computation and its viability for practical use. The paper also seeks to understand and state the challenges and concepts of Secure Multiparty Computation through the construction of a home loan calculation application. Encryption over Multi Party Computation (MPC) is done within 2 to 2.5 s. Up to 10 K addition operations, MPC system performs very well and most applications will be sufficient within 10K additions.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - School of Sciences (6 Sep 2019 -)
Date Deposited: 14 Aug 2020 06:08
Last Modified: 09 Oct 2020 00:02
Uncontrolled Keywords: Privacy; Secure multiparty computation; FRamework for Efficient Secure COmputation (FRESCO)
Fields of Research (2008): 08 Information and Computing Sciences > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified
Identification Number or DOI: https://doi.org/10.1007/978-3-030-03405-4_7
URI: http://eprints.usq.edu.au/id/eprint/37871

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