Let A be a finite plaintext alphabet and V be a cypher alphabet with the same cardinality as A. In all one-to-one substitution cyphers, there exists the property that each element in V maps onto exactly one element in A and vice versa. This mapping of V onto A is represented by a function T*, which maps any V onto some A A (i.e., T*(r) — A). In this correspondence, we consider the problem of learning the mapping of T* (or its inverse (T*)-1) by processing a sequence of cypher text. The fastest reported method to achieve this is an elegant relaxation scheme due to Peleg et al. [8], [9] that utilizes the statistical information contained in the unigrams and trigrams of the plaintext language. In this correspondence, we present a new learning automaton solution to the problem called the cypher learning automaton (CLA). The proposed scheme is fast, and the advantages of the scheme in terms of time and space requirements over the relaxation method have been listed. The correspondence contains simulation results comparing both cypher-breaking techniques.

Additional Metadata
Keywords Crytography, learning automata, relaxation methods, substitution cyphers
Persistent URL dx.doi.org/10.1109/34.192492
Journal IEEE Transactions on Pattern Analysis and Machine Intelligence
Citation
Oommen, J, & Zgierski, J.R. (J. R.). (1993). Breaking Substitution Cyphers Using Stochastic Automata. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(2), 185–192. doi:10.1109/34.192492