Unconditionally secure distributed oblivious polynomial evaluation

Cianciullo, Louis, and Ghodosi, Hossein (2019) Unconditionally secure distributed oblivious polynomial evaluation. In: Lecture Notes in Computer Science (11396) pp. 132-142. From: Information Security and Cryptology – ICISC 2018, 28-30 November 2018, Seoul, South Korea.

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Oblivious polynomial evaluation (OPE) was first introduced by Naor and Pinkas in 1999. An OPE protocol involves a receiver, R who holds a value, α and a sender, S with a private polynomial, f(x). OPE allows R to compute f(α) without revealing either α or f(x). Since its inception, OPE has been established as an important building block in many distributed applications. In this article we investigate a method of achieving unconditionally secure distributed OPE (DOPE) in which the function of the sender is distributed amongst a set of n servers. Specifically, we introduce a model for DOPE based on the model for distributed oblivious transfer (DOT) described by Blundo et al. in 2002. We then describe a protocol that achieves the security defined by our model. Our DOPE protocol is efficient and achieves a high level of security. Furthermore, our proposed protocol can also be used as a DOT protocol with little to no modification.

Item ID: 57718
Item Type: Conference Item (Research - E1)
ISBN: 978-3-030-12146-4
ISSN: 0302-9743
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Copyright Information: © Springer Nature Switzerland AG 2019
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A version of this publication was included as Chapter 4 of the following PhD thesis: Cianciullo, Louis (2022) Investigation of unconditionally secure multi-party computation. PhD thesis, James Cook University, which is available Open Access in ResearchOnline@JCU. Please see the Related URLs for access.

Funders: Australian Government Research Training Program
Date Deposited: 18 Sep 2019 02:41
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4613 Theory of computation > 461301 Coding, information theory and compression @ 70%
46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460401 Cryptography @ 30%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970108 Expanding Knowledge in the Information and Computing Sciences @ 100%
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