Abstract
Leakage assessment is the most common approach applied for assessing side-channel information leakage and validating the effectiveness of side-channel countermeasures. Established evaluation approaches are usually based on Test Vector Leakage Assessment (TVLA) that deployed in a divide and conquer flow with offline computations, which causes two apparent shortcomings in required memory and time. In this paper, a lightweight framework of online leakage assessment is proposed. The problems were analyzed and the evaluation approach was further validated with a Field Programmable Gate Array (FPGA). The experimental results show that it can implement online processing on newly collected data, and instantly stop to give the result when detecting credible leakage. The online leakage assessment can significantly economize on memory and time. It has good performance when there is limited memory or real-time evaluations are needed.
The authors would like to thank Information Science Laboratory Center of USTC for the hardware/software services. This work was supported by National Natural Science Foundation of China (Nos. 61972370 and 61632013), Fundamental Research Funds for Central Universities in China (No. WK3480000007).
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Shi, Z. et al. (2020). Research on Online Leakage Assessment. In: Qin, P., Wang, H., Sun, G., Lu, Z. (eds) Data Science. ICPCSEE 2020. Communications in Computer and Information Science, vol 1258. Springer, Singapore. https://doi.org/10.1007/978-981-15-7984-4_11
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