A Chi-Square Side-Channel Energy Leakage Assessment Method Based on HC Test

The chi-square side-channel energy leakage assessment method is significantly affected by noise. Moreover, due to the large number of sampling points in energy traces, misjudgments are difficult to avoid, resulting in a higher number of energy samples required to detect leakage. To address this, a chi-square leakage assessment method based on Higher Criticism (HC) is proposed. This method applies the HC process to the p-value sequence obtained from chi-square tests, comparing the expected p-value sequence (under no leakage) with the actual p-value sequence distribution. Leakage is identified when the difference between the two distributions is sufficiently large. Validation experiments were conducted using simulated energy data, the public dataset DP A Contest v4.2, and Chipwhisperer self-measured energy data. Results demonstrate that under a fixed signal-to-noise ratio (SNR) of energy data, the proposed method reduces the number of samples required for leakage detection compared to other methods, with reductions of up to 25.5%, 31.9%, and 23.2%, respectively. Thus, the proposed method effectively mitigates the challenges of noise sensitivity and misjudgment in chi-square leakage assessment.