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LDA-Based Clustering as a Side-Channel Distinguisher

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Radio Frequency Identification and IoT Security (RFIDSec 2016)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10155))

Abstract

Side-channel attacks put the security of the implementations of cryptographic algorithms under threat. Secret information can be recovered by analyzing the physical measurements acquired during the computations and using key recovery distinguishing functions to guess the best candidate. Several generic and model based distinguishers have been proposed in the literature. In this work we describe two contributions that lead to better performance of side-channel attacks in challenging scenarios. First, we describe how to transform the physical leakage traces into a new space where the noise reduction is near-optimal. Second, we propose a new generic distinguisher that is based upon minimal assumptions. It approaches a key distinguishing task as a problem of classification and ranks the key candidates according to the separation among the leakage traces. We also provide experiments and compare their results to those of the Correlation Power Analysis (CPA). Our results show that the proposed method can indeed reach better success rates even in the presence of significant amount of noise.

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Acknowledgments

This work has been funded partially by Riscure BV through the Internship@Riscure program, by the Dutch government and the Netherlands Technology Foundation STW through project 13499 - TYPHOON & ASPASIA, project 12624 - SIDES, and by the Netherlands Organization for Scientific Research NWO through project 628.001.007 - ProFIL.

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Authors and Affiliations

  1. Riscure BV, Delftechpark 49, 2628 XJ, Delft, The Netherlands

    Rauf Mahmudlu, Valentina Banciu & Ileana Buhan

  2. Digital Security Group, Radboud University, Nijmegen, The Netherlands

    Rauf Mahmudlu & Lejla Batina

Authors
  1. Rauf Mahmudlu
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  2. Valentina Banciu
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  3. Lejla Batina
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  4. Ileana Buhan
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Corresponding author

Correspondence to Rauf Mahmudlu .

Editor information

Editors and Affiliations

  1. City University of Hong Kong, Hong Kong, China

    Gerhard P. Hancke

  2. University of London, Egham, United Kingdom

    Konstantinos Markantonakis

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Mahmudlu, R., Banciu, V., Batina, L., Buhan, I. (2017). LDA-Based Clustering as a Side-Channel Distinguisher. In: Hancke, G., Markantonakis, K. (eds) Radio Frequency Identification and IoT Security. RFIDSec 2016. Lecture Notes in Computer Science(), vol 10155. Springer, Cham. https://doi.org/10.1007/978-3-319-62024-4_5

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  • DOI: https://doi.org/10.1007/978-3-319-62024-4_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62023-7

  • Online ISBN: 978-3-319-62024-4

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