An Evaluation of Power Side-Channel Resistance for RNS Secure Logic

Abstract

In this paper, residue number system (RNS) based logic is proposed as a protection against power side-channel attacks. Every input to RNS logic is encrypted as a share of the original input in the residue domain through modulus values. Most existing countermeasures enhance side-channel privacy by making the power trace statistically indistinguishable. The proposed RNS logic provides cryptographic privacy that also offers side-channel resistance. It also offers side-channel privacy by mapping different input bit values into similar bit encodings for the shares. This property is also captured as a symmetry measure in the paper. This side-channel resistance of the RNS secure logic is evaluated analytically and empirically. An analytical metric is developed to capture the conditional probability of the input bit state given the residue state visible to the adversary, but derived from hidden cryptographic secrets. The transition probability, normalized variance, and Kullback–Leibler (KL) divergence serve as side-channel metrics. The results show that our RNS secure logic provides better resistance against high-order side-channel attacks both in terms of power distribution uniformity and success rates of machine learning (ML)-based power side-channel attacks. We performed SPICE simulations on Montgomery modular multiplication and Arithmetic-style modular multiplication using the FreePDK 45 nm Technology library. The simulation results show that the side-channel security metrics using KL divergence are 0.0204 for Montgomery and 0.0020 for the Arithmetic-style implementation. This means that Arithmetic-style implementation has better side-channel resistance than the Montgomery implementation. In addition, we evaluated the security of the AES encryption with RNS secure logic on a Spartan-6 FPGA Board. Experimental results show that the protected AES circuit offers 79% higher resistance compared to the unprotected AES circuit.

Residue Number System (RNS) and Power Distribution Network Topology-Based Mitigation of Power Side-Channel Attacks

“…Dual rail logic provides strong side-channel privacy, but no cryptographic privacy. The RNS logic [21,22] combines both side-channel privacy and cryptographic privacy. There is an average reduction of 25% in the adversary's machine learning success rate in leaking a block encryption secret with the RNS logic.…”

Countermeasures against hardware attack using power-based information leakage

“…The resilience characteristics of the RNS secure circuit and its adversarial complexity are reported in this chapter. This chapter is based on two articles, one published in VLSID Selvam and Tyagi (2018) and the other in Selvam and Tyagi (2022a).…”