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Distributed power analysis attack on SM4 encryption chip.

Haoran Gong1, Tailiang Ju2

  • 1UESTC, No. 2006 Xiyuan Avenue, Chengdu, 611730, Sichuan, China.

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|January 10, 2024
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Summary
This summary is machine-generated.

This study introduces a distributed energy analysis attack for encryption chips, significantly reducing cracking time and improving accuracy. The novel method enhances security analysis of SM4 and AES algorithms against power consumption side-channel attacks.

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Cryptography

Background:

  • Encryption chips are crucial for data security, utilizing algorithms like China's SM4 and international AES.
  • Power consumption side-channel attacks, including Differential Power Analysis (DPA) and machine learning, are prevalent threats.
  • Existing methods face limitations in accuracy and efficiency for key recovery.

Purpose of the Study:

  • To present a novel distributed energy analysis attack based on Correlation Power Analysis (CPA).
  • To enhance the efficiency and accuracy of cryptanalysis against encryption chips.
  • To reduce the computational resources and time required for key recovery.

Main Methods:

  • A distributed energy analysis attack approach using Correlation Power Analysis (CPA).
  • Dividing power consumption data into 16 subsets, each corresponding to 8 key bytes.
  • Training each subset separately and reducing data dimensionality to 100.

Main Results:

  • Achieved a 76% decrease in cracking time and a 3% improvement in accuracy.
  • A 256 classification model directly cracked 128-bit passwords with 28% success using only 1 power trace.
  • Demonstrated effectiveness against SM4 and AES encryption standards.

Conclusions:

  • The distributed energy analysis attack offers a more efficient and accurate method for cryptanalysis.
  • This approach improves the security assessment of encryption chips against side-channel attacks.
  • Further research can explore optimizations for real-time cryptanalysis and broader algorithm applications.