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Leakage Fingerprints: A Non-negligible Vulnerability in Side-Channel Analysis

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Published:30 May 2016Publication History

ABSTRACT

Low-entropy masking schemes and shuffling technique are two common countermeasures against traditional side-channel analysis. Improved Rotating S-box Masking (RSM) is a combination of both countermeasures and is implemented by DPA contest committee to improve the software security level of AES-128. Compared with the original version, improved RSM mainly introduces both the offset and shuffle array as security foundations to counteract the existing attacks. In this paper, we first point out a general vulnerability referred to as "leakage fingerprints" and make use of it to successfully crack the offset array with 100% accuracy, which breaks down the masking countermeasure in the first step. Then, we show that cracking the shuffle array is still feasible but not necessary since several other vulnerabilities in the implementation level can be exploited to bypass the shuffle countermeasure directly. By selectively combining all these vulnerabilities, a dozen of attacks can be put forward, and we perform two of them as examples to verify their effectiveness. Official evaluation results show that, both attacks submitted by us are practical and feasible, and also operate with high efficiency. In terms of two major performance metrics, our best scheme requires 4 traces to reveal the AES master key with 80% Global Success Rate (GSR) and only 2 traces are enough to reduce the Maximum Partial Guessing Entropy (PGE) under 10.

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                          cover image ACM Conferences
                          ASIA CCS '16: Proceedings of the 11th ACM on Asia Conference on Computer and Communications Security
                          May 2016
                          958 pages
                          ISBN:9781450342339
                          DOI:10.1145/2897845

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                          • Published: 30 May 2016

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                          ASIA CCS '16 Paper Acceptance Rate73of350submissions,21%Overall Acceptance Rate418of2,322submissions,18%
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