DARNS:A randomized multi-modulo RNS architecture for double-and-add in ECC to prevent power analysis side channel attacks

Abstract

Security in embedded systems is of critical importance since most of our secure transactions are currently made via credit cards or mobile phones. Power analysis based side channel attacks have been proved as the most successful attacks on embedded systems to retrieve secret keys, allowing impersonation and theft. State-of-the-art solutions for such attacks in Elliptic Curve Cryptography (ECC), mostly in software, hinder performance and repeatedly attacked using improved techniques. To protect the ECC from both simple power analysis and differential power analysis, as a hardware solution, we propose to take advantage of the inherent parallelization capability in Multi-modulo Residue Number Systems (RNS) architectures to obfuscate the secure information. Random selection of moduli is proposed to randomly choose the moduli sets for each key bit operation. This solution allows us to prevent power analysis, while still providing all the benefits of RNS. In this paper, we show that Differential Power Analysis is thwarted, as well as correlation analysis.