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Efficient coding for secure computing with additively-homomorphic encrypted data

Efficient coding for secure computing with additively-homomorphic encrypted data A framework is introduced for efficiently computing with encrypted data. We assume a semi-honest security model with two computing parties. Two different coding techniques are used with additively homomorphic encryption, such that many values can be put into one large encryption, and additions and multiplications can be performed on all values simultaneously. For more complicated operations such as comparisons and equality tests, bit-wise secret sharing is proposed as an additional technique that has a low computational and communication complexity, and which allows for precomputing. The framework is shown to significantly improve the computational complexity of state-of-the-art solutions on generic operations such as secure comparisons and secure set intersection. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Applied Cryptography Inderscience Publishers

Efficient coding for secure computing with additively-homomorphic encrypted data

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1753-0563
eISSN
1753-0571
DOI
10.1504/IJACT.2020.107160
Publisher site
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Abstract

A framework is introduced for efficiently computing with encrypted data. We assume a semi-honest security model with two computing parties. Two different coding techniques are used with additively homomorphic encryption, such that many values can be put into one large encryption, and additions and multiplications can be performed on all values simultaneously. For more complicated operations such as comparisons and equality tests, bit-wise secret sharing is proposed as an additional technique that has a low computational and communication complexity, and which allows for precomputing. The framework is shown to significantly improve the computational complexity of state-of-the-art solutions on generic operations such as secure comparisons and secure set intersection.

Journal

International Journal of Applied Cryptography – Inderscience Publishers

Published: Jan 1, 2020

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