Abstract-A low-transition test pattern generator, called the low-transition linear feedback shift register (LT-LFSR), is proposed to reduce the average and peak power of a circuit during test by reducing the transitions among patterns. Transitions are reduced in two dimensions: 1) between consecutive patterns (fed to a combinational only circuit) and 2) between consecutive bits (sent to a scan chain in a sequential circuit). LT-LFSR is independent of circuit under test and flexible to be used in both BIST and scan-based BIST architectures. The proposed architecture increases the correlation among the patterns generated by LT-LFSR with negligible impact on test length. The experimental results for the ISCAS'85 and '89 benchmarks confirm up to 77 percent and 49 percent reduction in average and peak power, respectively.
The areas of hardware security and trust have experienced major growth over the past several years. However, research in Trojan detection and prevention lacks standard benchmarks and measurements, resulting in inconsistent research outcomes, and ambiguity in analyzing strengths and weaknesses in the techniques developed by different research teams and their advancements to the state-of-the-art. We have developed innovative methodologies that, for the first time, more effectively address the problem. We have developed a vulnerability analysis flow. The flow determines hardto-detect areas in a circuit that would most probably be used for Trojan implementation to ensure a Trojan goes undetected during production test and extensive functional test analysis. Furthermore, we introduce the Trojan detectability metric to quantify Trojan activation and effect. This metric offers a fair comparison for analyzing weaknesses and strengths of Trojan detection techniques. Using these methodologies, we have developed a large number of trust benchmarks that are available for use by the public, as well as researchers and practitioners in the field.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.