Genetic algorithms (GAs) are a class of optimization algorithms. GAs attempt to solve
problems through modeling a simplified version of genetic processes. There are many
problems for which a GA approach is useful. It is, however, undetermined if cryptanalysis
is such a problem.
Therefore, this work explores the use of GAs in cryptography. Both traditional cryptanalysis
and GA-based methods are implemented in software. The results are then compared
using the metrics of elapsed time and percentage of successful decryptions. A determination
is made for each cipher under consideration as to the validity of the GA-based
approaches found in the literature. In general, these GA-based approaches are typical of
Of the genetic algorithm attacks found in the literature, totaling twelve, seven were
re-implemented. Of these seven, only three achieved any success. The successful attacks
were those on the transposition and permutation ciphers by Matthews , Clark , and
Gr¨undlingh and Van Vuuren , respectively. These attacks were further investigated in
an attempt to improve or extend their success. Unfortunately, this attempt was unsuccessful,
as was the attempt to apply the Clark  attack to the monoalphabetic substitution cipher
and achieve the same or indeed any level of success.