Benchmarking Privacy Preserving Scientific Operations

Abdelrahaman Aly; Nigel P.  Smart

Paper 2019/354

Benchmarking Privacy Preserving Scientific Operations

Abdelrahaman Aly and Nigel P. Smart

Abstract

In this work, we examine the efficiency of protocols for secure evaluation of basic mathematical functions ($\mathtt{sqrt}, \mathtt{sin}, \mathtt{arcsin}$, amongst others), essential to various application domains. e.g., Artificial Intelligence. Furthermore, we have incorporated our code in state-of-the-art Multiparty Computation (MPC) software, so we can focus on the algorithms to be used as opposed to the underlying MPC system. We make use of practical approaches that, although, some of them, theoretically can be regarded as less efficient, can, nonetheless, be implemented in such software libraries without further adaptation. We focus on basic scientific operations, and introduce a series of data-oblivious protocols based on fixed point representation techniques. Our protocols do not reveal intermediate values and do not need special adaptations from the underlying MPC protocols. We include extensive computational experimentation under various settings and MPC protocols.

Note: minor typos fixed on algorithm app_sq

Metadata

Available format(s): PDF
Category: Cryptographic protocols
Publication info: Published elsewhere. Minor revision. ACNS 2019
Contact author(s): nigel smart @ kuleuven be
Abdelrahaman Aly @ esat kuleuven be
History: 2021-08-03: last of 2 revisions; 2019-04-03: received; See all versions
Short URL: https://ia.cr/2019/354
License: CC BY

BibTeX

@misc{cryptoeprint:2019/354,
      author = {Abdelrahaman Aly and Nigel P.  Smart},
      title = {Benchmarking Privacy Preserving Scientific Operations},
      howpublished = {Cryptology {ePrint} Archive, Paper 2019/354},
      year = {2019},
      url = {https://eprint.iacr.org/2019/354}
}