2012
DOI: 10.1109/tifs.2011.2174984
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Information-Theoretic Approach to Optimal Differential Fault Analysis

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Cited by 50 publications
(37 citation statements)
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“…Small differences in the fault models might crucially affect the capabilities and the complexity of the attacks [27]. Today, there is a wide range of literature on DFAs, e.g., [16,107,145].…”
Section: Symmetric Cryptographymentioning
confidence: 99%
“…Small differences in the fault models might crucially affect the capabilities and the complexity of the attacks [27]. Today, there is a wide range of literature on DFAs, e.g., [16,107,145].…”
Section: Symmetric Cryptographymentioning
confidence: 99%
“…For everyk, an fault value e [m],(i, j),k is obtained from every injection m. Because of the SubBytes operation, the e [m],(i, j),k is quasi-random for wrong key hypotheses [48]. The fault entropy gives the entropy of the faults which is a first-order effect.…”
Section: Fault Entropy (Fe)mentioning
confidence: 99%
“…H(∆) = H < b. Given the non-linear property of the S-box the corresponding set of errors δ i K =K * computed for all the pairs (C i ,C i ) with a wrong key shall be uniformly distributed [22]. The set of errors δ i K=K * computed with the correct key shall be non uniformly distributed; hence, the error entropy can be used for key selection.…”
Section: B Ciphertext-based Attacks Against Spnmentioning
confidence: 99%
“…A given number of randomly generated multiple bit-reset faults were injected into a randomly generated variable x and the number of different faulty values Y were used to determine the Hamming weight of the variable using formula (22). The total number of successfully determined Hamming weights was recorded for 10 5 trials and the success rate was computed for each number of faults as shown on Figure 4.…”
Section: B Hamming Weight Computationmentioning
confidence: 99%