2 research outputs found

    Analysis of Software Implemented Low Entropy Masking Schemes

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    Low Entropy Masking Schemes (LEMS) are countermeasure techniques to mitigate the high performance overhead of masked hardware and software implementations of symmetric block ciphers by reducing the entropy of the mask sets. The security of LEMS depends on the choice of the mask sets. Previous research mainly focused on searching balanced mask sets for hardware implementations. In this paper, we find that those balanced mask sets may have vulnerabilities in terms of absolute difference when applied in software implemented LEMS. The experiments verify that such vulnerabilities certainly make the software LEMS implementations insecure. To fix the vulnerabilities, we present a selection criterion to choose the mask sets. When some feasible mask sets are already picked out by certain searching algorithms, our selection criterion could be a reference factor to help decide on a more secure one for software LEMS

    Near Collision Side Channel Attacks

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    Side channel collision attacks are a powerful method to exploit side channel leakage. Otherwise than a few exceptions, collision attacks usually combine leakage from distinct points in time, making them inherently bivariate. This work introduces the notion of near collisions to exploit the fact that values depending on the same sub-key can have similar while not identical leakage. We show how such knowledge can be exploited to mount a key recovery attack. The presented approach has several desirable features when compared to other state-of-the-art collision attacks: Near collision attacks are truly univariate. They have low requirements on the leakage functions, since they work well for leakages that are linear in the bits of the targeted intermediate state. They are applicable in the presence of masking countermeasures if there exist distinguishable leakages, as in the case of leakage squeezing. Results are backed up by a broad range of simulations for unprotected and masked implementations, as well as an analysis of the measurement set provided by DPA Contest v4
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