• Title/Summary/Keyword: Supersingular Isogeny Key Encapsulation

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Deep Learning Based Side-Channel Analysis for Recent Masking Countermeasure on SIKE (SIKE에서의 최신 마스킹 대응기법에 대한 딥러닝 기반 부채널 전력 분석)

  • Woosang Im;Jaeyoung Jang;Hyunil Kim;Changho Seo
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.151-164
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    • 2023
  • Recently, the development of quantum computers means a great threat to existing public key system based on discrete algebra problems or factorization problems. Accordingly, NIST is currently in the process of contesting and screening PQC(Post Quantum Cryptography) that can be implemented in both the computing environment and the upcoming quantum computing environment. Among them, SIKE is the only Isogeny-based cipher and has the advantage of a shorter public key compared to other PQC with the same safety. However, like conventional cryptographic algorithms, all quantum-resistant ciphers must be safe for existing cryptanlysis. In this paper, we studied power analysis-based cryptographic analysis techniques for SIKE, and notably we analyzed SIKE through wavelet transformation and deep learning-based clustering power analysis. As a result, the analysis success rate was close to 100% even in SIKE with applied masking response techniques that defend the accuracy of existing clustering power analysis techniques to around 50%, and it was confirmed that was the strongest attack on SIKE.