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    The search method based on soft computing for linear cryptanalysis of block ciphers
    (Maltepe Üniversitesi, 2009) Tabatabaei, Amir
    Optimization, combinatorial and in general modeling methods are the concepts in applied mathematics which if considered alone and purely they can not be used in solving real problems. The better establishing a relation with other fields the more applications can be gained. In this article two kinds of optimization methods which have a lot of applications in cryptography will be proposed: The first one is dealing with the advantages of using high performance Genetic Algorithm in comparison to some analytic methods in cryptanalysis of block ciphers and the second one is a model represented by a weighted graph which must be optimized by some soft computing methods because of its high complexity. At the end of this article some other useful applications of these ideas along with a practical done example on a block cipher will be represented.
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    A survey on search methods based on soft computing for cryptanalysis of block ciphers
    (Maltepe Üniversitesi, 2009) Tabatabaei, Amir
    In this paper, a survey on the applications of soft computing in cryptanalysis of block ciphers along with some case studies is presented. The nature of cryptanalysis problems is involved with huge search domain which is a key point in providing the security of primitives. Regarding to this property, tracing analytic solutions will frustrate the attacker due to complexity theory. We propose two kinds of optimization models which have a lot of applications in cryptography: The first one is dealing with a high performance Genetic Algorithm in comparison to some analytic methods in cryptanalysis of block ciphers and the second one is a model represented by a weighted graph which must be optimized by some soft computing methods because of its high complexity. We will show the results gained by suggested methods in finding the differential and linear characteristics of a well-known block cipher. The cost of time, memory, and data complexity of the proposed method in comparison to analytic methods validates the priority of them.