A Programmable SoC Implementation of the DGK Cryptosystem for Privacy-Enhancing Technologies

Abstract

Additively homomorphic encryption has many applications in privacy-enhancing technologies because it allows a cloud service provider to perform simple computations with users’ data without learning the contents. The performance overhead of additively homomorphic encryption is a major obstacle for practical adaptation. Hardware accelerators could reduce this overhead substantially. In this paper, we present an implementation of the DGK cryptosystem for programmable systems-on-chip and evaluate it in real hardware. We demonstrate its efficiency for accelerating privacy-enhancing technologies by using it for computing squared Euclidean distances between a user’s input and a server’s database. We also provide comparisons with a recent implementation of Paillier cryptosystem and show that DGK offers major speedups. This work represents the first implementation of the DGK cryptosystem that uses hardware acceleration and demonstrates that the DGK benefits greatly from the hardware/software codesign approach.