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Overcoming Significant Noise: Correlation-Template-Induction Attack

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Information Security Practice and Experience (ISPEC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 7232))

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Abstract

Due to low Signal to Noise Ratio (SNR) in general experimental environments, previous attack methods such as correlation power analysis (CPA) do not always screen out the correct key value. Sometimes the success rate of the attack is so slight that we have to find other ways to make certain of the prosperity. In this paper, rather than adopting the traditional means of singling out a single key value, we suggest a way of setting up a threshold for the attack. Accordingly, we propose a feasible method to filter the inherently enlarging candidate key space, which is called correlation-template-induction attack. The method contains three steps: First, we apply a variation of CPA and get a set of candidate key values. Then, we filter the candidate key space with template attack, which is easy to implement and requires encryptions of just a few input data to screen out the correct key. Next, to achieve optimal of our attack, we mix the concept of induction together with our attack. The experimental results given in this article on an AES smart card implementation guarantee the effectiveness of our method.

Supported by the National Natural Science Foundation of China (Grant No. 61133013 and 60931160442) and the Tsinghua University Initiative Scientific Research Program (No.2009THZ01002, No.20111080970).

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Wang, A., Chen, M., Wang, Z., Ding, Y. (2012). Overcoming Significant Noise: Correlation-Template-Induction Attack. In: Ryan, M.D., Smyth, B., Wang, G. (eds) Information Security Practice and Experience. ISPEC 2012. Lecture Notes in Computer Science, vol 7232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29101-2_27

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  • DOI: https://doi.org/10.1007/978-3-642-29101-2_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29100-5

  • Online ISBN: 978-3-642-29101-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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