Publicado en línea: 15 ago 2019
Páginas: 39 - 60
Recibido: 30 oct 2018
DOI: https://doi.org/10.2478/tmmp-2019-0005
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© 2019 Eugen Antal et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
The most commonly used methods for solving classical (historical) ciphers are based on global optimization (meta-heuristic methods). Despite the fact that global optimization is a well-studied problem, in the case of classical ciphers, there are still many open questions such as the construction of fitness functions or efficient transformation of the cryptanalysis (breaking attempt) to an optimization problem. Therefore the transformation of a cryptanalytical task to an optimization problem and the choice of a suitable fitness function form an important part of the topic. In this paper, we focus on the simple columnar transposition in depth. Our main contribution is a detailed analysis and comparison of different fitness functions, fitness landscape analysis and solving experiments.