An Improved Method of Side Channel Leak Assessment for Cryptographic Algorithm | Web and Big Data (2024)

An Improved Method ofSide Channel Leak Assessment forCryptographic Algorithm | Web and Big Data (2)

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  • f*ckiang Lu China Quality Certification Center South China Laboratory, Guangzhou, China

    China Quality Certification Center South China Laboratory, Guangzhou, China

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  • Weijian Li https://ror.org/02pcb5m77Guangdong Polytechnic Normal University, Guangzhou, China

    https://ror.org/02pcb5m77Guangdong Polytechnic Normal University, Guangzhou, China

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  • Zanyu Huang https://ror.org/02pcb5m77Guangdong Polytechnic Normal University, Guangzhou, China

    https://ror.org/02pcb5m77Guangdong Polytechnic Normal University, Guangzhou, China

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  • Chuanlu Chen China Quality Certification Center South China Laboratory, Guangzhou, China

    China Quality Certification Center South China Laboratory, Guangzhou, China

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  • Peng Chen China Quality Certification Center South China Laboratory, Guangzhou, China

    China Quality Certification Center South China Laboratory, Guangzhou, China

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Web and Big Data: 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part IVOct 2023Pages 328–342https://doi.org/10.1007/978-981-97-2421-5_22

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Web and Big Data: 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part IV

An Improved Method ofSide Channel Leak Assessment forCryptographic Algorithm

Pages 328–342

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An Improved Method ofSide Channel Leak Assessment forCryptographic Algorithm | Web and Big Data (3)

Abstract

As a standard method of side channel leak assessment, TVLA is a popular research direction of side channel attack. TVLA mainly conducts leak assessment based on Welch’s t-test or paired t-test, but in some evaluation scenarios, different leak assessment results may appear in the two hypothesis tests. Firstly, the modified relationship between the two kinds of t-tests is studied in theory, and then it is pointed out that the paired t-test is better when there is a positive correlation between the two groups of sampled populations to be evaluated, while the correcting two-sample t-test is needed when there is an independent or negative correlation. Secondly, it is verified by experiments that in common experimental scenarios, such as noise of common measuring equipment, temperature fluctuation and the choice of cross-input plaintext sequence will lead to positive correlation between samples, especially in the first two scenarios, the paired t-test can play a fast, efficient and robust role. Theoretical analysis and experimental results show that the method of mutual correction by two hypothesis tests ensures the accuracy and efficiency of side channel leakage assessment.

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      An Improved Method ofSide Channel Leak Assessment forCryptographic Algorithm | Web and Big Data (43)

      Web and Big Data: 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part IV

      Oct 2023

      538 pages

      ISBN:978-981-97-2420-8

      DOI:10.1007/978-981-97-2421-5

      • Editors:
      • Xiangyu Song

        https://ror.org/03qdqbt06Peng Cheng Laboratory, Shenzhen, China

        ,
      • Ruyi Feng

        China University of Geosciences, Wuhan, China

        ,
      • Yunliang Chen

        https://ror.org/04gcegc37China University of Geosciences, Wuhan, China

        ,
      • Jianxin Li

        https://ror.org/02czsnj07Deakin University, Burwood, VIC, Australia

        ,
      • Geyong Min

        University of Exeter, Exeter, UK

      © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024

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          Springer-Verlag

          Berlin, Heidelberg

          Publication History

          • Published: 12 May 2024

          Author Tags

          • TVLA
          • paired t-test
          • correcting two-sample t-tests
          • assessment of side channel
          • side channel attack

          Qualifiers

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          • An Improved Method ofSide Channel Leak Assessment forCryptographic Algorithm | Web and Big Data (44)

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