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

Over the past decade, significant research has been performed on power side-channel mitigation techniques. Logic families based on secret sharing schemes, such as t-private logic, that serve to secure cryptographic implementations against power side-channel attacks represent one such countermeasure. These mitigation techniques are applicable at various design abstraction levels—algorithm, architecture, logic, physical, and gate levels. One research question is when can the two mitigation techniques from different design abstraction levels be employed together gainfully? We explore this notion of the orthogonality of two mitigation techniques with respect to the RNS secure logic, a logic level power side-channel mitigation technique, and power distribution network (PDN), with the decoupling capacitance, a mitigation technique at physical level. Machine learning (ML) algorithms are employed to measure the effectiveness of power side-channel attacks in terms of the success rate of the adversary. The RNS protected LED block cipher round function is implemented as the test circuit in both tree-style and grid-style PDN using the FreePDK 45 nm technology library. The results show that the success rate of an unsecured base design 68.96% for naive Bayes, 67.44% with linear discriminant analysis, 67.51% for quadratic discriminant analysis, and 66.58% for support vector machine. It is reduced to a success rate of 19.68% for naive Bayes, 19.62% with linear discriminant analysis, 19.10% for quadratic discriminant analysis, and 10.54% in support vector machine. Grid-type PDN shows a slightly better reduction in success rate compared to the tree-style PDN.