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Volume 15 Issue 3

Pixel-Batched Homomorphic Encryption for Secure-at-Rest Image Convolution

Chris R. Giannella^(a),(*), Adrian V. Mariano^(a), James H. Tanis^(a)

Transactions on Data Privacy 15:3 (2022) 193 - 211

Abstract, PDF

(a) The MITRE Corp., 7515 Colshire Dr. McLean, VA 22102, USA.

e-mail:cgiannella @mitre.org; adrian @mitre.org; jhtanis @mitre.org

Abstract

We consider a secure image processing workflow where the data owner keeps their raw imagery encrypted at all times to reduce the risk of sensitive information exposure in the event of a data breach. However, the owner also makes unencrypted, convolution-filtered versions of the images available to consumers (upon request) who specify a convolution kernel. To acheive this workflow, we utilize homomorphic encryption through the Paillier cryptosystem. We start by considering a simple approach where each pixel is encrypted separately. To reduce overall computation, we next develop a more complex approach where vectors of pixels are batched before encryption (an idea applied by others to different image processing algorithms). Through simulation experiments, we observe the approach involving batching to require one to two orders of magnitude less computation time.

^* Corresponding author.

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