Paper 2023/008

AutoPOI: Automated Points Of Interest Selection for Side-channel Analysis

Mick G.D. Remmerswaal, Leiden University
Lichao Wu, Delft University of Technology
Sébastien Tiran
Nele Mentens, KU Leuven, Leiden University

Template attacks~(TAs) are one of the most powerful Side-Channel Analysis~(SCA) attacks. The success of such attacks relies on the effectiveness of the profiling model in modeling the leakage information. A crucial step for TA is to select relevant features from the measured traces, often called Points Of Interest~(POIs), to extract the leakage information. Previous research indicates that properly selecting the input leaking features could significantly increase the attack performance. However, due to the presence of SCA countermeasures and advancements in technology nodes, such features become increasingly difficult to extract with conventional approaches such as Principle Component Analysis (PCA) and the Sum Of Squared pairwise T-differences based method (SOST). This work proposes a framework, AutoPOI, based on proximal policy optimization to automatically find, select, and scale down features. The input raw features are first grouped into small regions. The best candidates selected by the framework are further scaled down with an online-optimized dimensionality reduction neural network. Finally, the framework rewards the performance of these features with the results of TA. Based on the experimental results, the proposed framework can extract features automatically that lead to comparable state-of-the-art performance on several commonly used datasets.

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Publication info
Side-channel AnalysisPoints Of Interest SelectionDeep Reinforcement LearningProximal Policy Optimization
Contact author(s)
mickremmerswaal @ gmail com
lichao wu9 @ gmail com
sebastien tiran @ gmail com
nele mentens @ kuleuven be
2023-01-03: approved
2023-01-02: received
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      author = {Mick G.D. Remmerswaal and Lichao Wu and Sébastien Tiran and Nele Mentens},
      title = {AutoPOI: Automated Points Of Interest Selection for Side-channel Analysis},
      howpublished = {Cryptology ePrint Archive, Paper 2023/008},
      year = {2023},
      note = {\url{}},
      url = {}
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