2008
DOI: 10.1007/978-3-540-89754-5_4
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New Results on the Key Scheduling Algorithm of RC4

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Cited by 27 publications
(34 citation statements)
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“…An improved key recovery approach with high probability of success as compared to [18] is achieved by Biham and Carmeli in [19], where authors have used differential equations instead of basic modular equations. The key recovery from state was further improved by authors in [20] by using equation solving approach. The technique discussed by authors in [20] is known to be the more efficient and faster approach form key recovery from state.…”
Section: Key Recovery From Statementioning
confidence: 99%
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“…An improved key recovery approach with high probability of success as compared to [18] is achieved by Biham and Carmeli in [19], where authors have used differential equations instead of basic modular equations. The key recovery from state was further improved by authors in [20] by using equation solving approach. The technique discussed by authors in [20] is known to be the more efficient and faster approach form key recovery from state.…”
Section: Key Recovery From Statementioning
confidence: 99%
“…The key recovery from state was further improved by authors in [20] by using equation solving approach. The technique discussed by authors in [20] is known to be the more efficient and faster approach form key recovery from state. Another key recovery approach was discussed in [21] which is again an improvement over the technique given by [19].…”
Section: Key Recovery From Statementioning
confidence: 99%
“…The results can be seen in Table 2. Very recently, Akgün, Kavak and Demirci [1] have developed new biases for RC4, combined them with previous results and provided a new key recovery algorithm from the internal state. It performs better than existing ones including ours.…”
Section: Theoremmentioning
confidence: 99%
“…It performs better than existing ones including ours. In particular, in a theorem similar to Theorem 1, they provide a lower bound for the probability that fully exploit the distribution of the noises, leaving a room to unify the biases from [1] with those from Theorem 1 in a future work.…”
Section: Theoremmentioning
confidence: 99%
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