A Countermeasure to Power Analysis Attack by Arbitrarily Injecting Multiple Types of Noise
Tomoaki Ukezono, Yui Koyanagi · 2023
As the Internet of Things (IoT) society develops, cryptographic security becomes even more important. However, side channel security remains a vulnerability without a definitive solution. We focus on power analysis attacks that estimate internal information from processor power consumption which is one of side channels and propose lightweight countermeasures to reduce the area and delay overhead compared with conventional countermeasures. This paper proposes a novel very large-scale integrated circuit (VLSI) design method, arbitrary noise injector (ANI), that randomly selected noise into vulnerable circuit to achieve improvement in tamper resistance. In our evaluation, it has been confirmed that ANI achieves comparable tamper resistance to the conventional design method, WDDL, with a small area overhead of approximately 7%.