Bias Cancellation of MixColumns
| Authors |
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| Publication date | 2022 |
| Host editors |
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| Book title | Security, Privacy, and Applied Cryptography Engineering |
| Book subtitle | 12th International Conference, SPACE 2022, Jaipur, India, December 9–12, 2022 : proceedings |
| ISBN |
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| ISBN (electronic) |
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| Series | Lecture Notes in Computer Science |
| Event | 12th International Conference on Security, Privacy, and Applied Cryptography Engineering, SPACE 2022 |
| Pages (from-to) | 70-80 |
| Number of pages | 11 |
| Publisher | Cham: Springer |
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| Abstract |
At COSADE’2020, Carré et al. established a novel bias-cancelling property of the AES MixColumns matrix that effectively corrects any skewed output distribution of a state byte due to a faulty substitution box. Consequently, any effected byte is rendered uniform upon passing through the MixColumns layer. In this work in progress paper, we revisit and generalize this result and in the process identify a large class of matrices that exhibit this bias cancellation phenomenon and conclude with a foray into how this property is advantageous in the design of countermeasures against Persistent Fault Injections. |
| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-031-22829-2_4 |
| Other links | https://www.scopus.com/pages/publications/85145261646 |
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