Linear Regression Attack with F-test: A New SCARE Technique for Secret Block Ciphers

  • Si Gao
  • Hua ChenEmail author
  • Wenling Wu
  • Limin Fan
  • Jingyi Feng
  • Xiangliang Ma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10052)


The past ten years have seen tremendous progress in the uptake of side channel analysis in various applications. Among them, Side Channel Analysis for Reverse Engineering (SCARE) is an especially fruitful area. Taking the side channel leakage into account, SCARE efficiently recovers secret ciphers in a non-destructive and non-intrusive manner. Unfortunately, most previous works focus on customizing SCARE for a certain type of ciphers or implementations. In this paper, we ask whether the attacker can loosen these restrictions and reverse secret block ciphers in a more general manner. To this end, we propose a SCARE based on Linear Regression Attack (LRA), which simultaneously detects and analyzes the power leakages of the secret encryption process. Compared with the previous SCAREs, our approach uses less a priori knowledge, covers more block cipher instances in a completely non-profiled manner. Moreover, we further present a complete SCARE flow with realistic power measurements of an unprotected software implementation. From traces that can barely recognize the encryption rounds, our experiments demonstrate how the underlying cipher can be recovered step-by-step. Although our approach still has some limitations, we believe it can serve as an alternative tool for reverse engineering in the future.


Linear Regression Attack SCARE F-test 



We would like to thank the anonymous reviewers for providing valuable comments. This work is supported by the National Basic Research Program of China (No.2013CB338002) and National Natural Science Foundation of China (No. 61272476, 61672509 and 61232009).


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Si Gao
    • 1
    • 2
  • Hua Chen
    • 1
    Email author
  • Wenling Wu
    • 1
  • Limin Fan
    • 1
  • Jingyi Feng
    • 1
    • 2
  • Xiangliang Ma
    • 1
    • 2
  1. 1.Trusted Computing and Information Assurance LaboratoryInstitute of Software, Chinese Academy of SciencesBeijingPeople’s Republic of China
  2. 2.University of Chinese Academy of SciencesBeijingPeople’s Republic of China

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