• Title/Summary/Keyword: Bitwise Collision

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Bitwise Collision Attack Based on Second-Order Distance

  • Wang, Danhui;Wang, An
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.3
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    • pp.1802-1819
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    • 2017
  • Correlation-enhanced collision attack has been proposed by Moradi et al. for several years. However, in practical operations, this method costs lots of time on trace acquisition, storage and averaging due to its bytewise collision detection. In this paper, we propose a bitwise collision attack based on second-order distance model. In this method, only 9 average traces are enough to finish a collision attack. Furthermore, two candidate models are given in this study to distinguish collisions, and the corresponding practical experiments are also performed. The experimental results indicate that the operation time of our attack is only 8% of that of correlation-enhanced collision attack, when the two success rates are both above 0.9.

Double Sieve Collision Attack Based on Bitwise Detection

  • Ren, Yanting;Wu, Liji;Wang, An
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.1
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    • pp.296-308
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    • 2015
  • Advanced Encryption Standard (AES) is widely used for protecting wireless sensor network (WSN). At the Workshop on Cryptographic Hardware and Embedded Systems (CHES) 2012, G$\acute{e}$rard et al. proposed an optimized collision attack and break a practical implementation of AES. However, the attack needs at least 256 averaged power traces and has a high computational complexity because of its byte wise operation. In this paper, we propose a novel double sieve collision attack based on bitwise collision detection, and an improved version with an error-tolerant mechanism. Practical attacks are successfully conducted on a software implementation of AES in a low-power chip which can be used in wireless sensor node. Simulation results show that our attack needs 90% less time than the work published by G$\acute{e}$rard et al. to reach a success rate of 0.9.