Cryptology ePrint Archive: Report 2016/1024

LDA-Based Clustering as a Side-Channel Distinguisher

Rauf Mahmudlu and Valentina Banciu and Lejla Batina and Ileana Buhan

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.

Category / Keywords: secret-key cryptography / Side-Channel Analysis, Data Transformation, Linear Discriminant Analysis, Differential Power Analysis, Electro-Magnetic Radiation, Signal to Noise Ratio

Original Publication (with minor differences): Proceedings of RFIDsec 2016

Date: received 28 Oct 2016

Contact author: raufmahmudlu at gmail com

Available format(s): PDF | BibTeX Citation

Version: 20161101:020003 (All versions of this report)

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