A Novel Self-referencing Approach Using Memory Power-up States for Detecting COTS SRAMs

The surge in counterfeit Integrated Circuits (ICs) in the electronics supply chain, particularly those reclaimed from recycled components of old and discarded electronics, poses a significant threat to our critical infrastructures. Unfortunately, this threat persists due to the absence of effective detection techniques. In pursuing a reliable detection method, a previous study introduced the idea of identifying recycled ICs using SRAM power-up states, leveraging the inherent symmetry in the logic states of 0s and 1s in newly manufactured SRAM cells. However, in SRAMs produced with older technology nodes, the reference parameter of 50% 1s is often less prominent due to systematic design variation biasing all cells in a specific direction. To address this challenge, this paper proposes a robust self-referencing approach for detecting recycled ICs. The power-up states of an IC under test are segmented into subregions for similarity analysis of the percent of 1s within them. Our study establishes that the percent of 1s in all subregions of a newly manufactured IC is statistically more similar to each other than that in a recycled IC. Our experimental results demonstrate a substantial rise in the standard deviation of the percent of 1s for subregions in the aged SRAM, occurring after just a few days of aging. This approach aims to enhance the reliability of counterfeit IC detection, particularly in the context of older technology nodes where conventional methods may fall short.