Classification and Identification of Classical Cipher Type Using Artificial Neural Networks
Ahmed Abd, Sufyan Al-Janabi
Journal of Information & Systems Management, Vol. 8, No. 3, 2018.
DOI: https://doi.org/10.6025/jism/2018/8/3/94-104
Link: http://www.dline.info/jism/fulltext/v8n3/jismv8n3_2.pdf
Abstract:
In this paper, the capability of classifying the main types of classical ciphers systems is presented using Artificial
Neural Networks (ANNs) starting from the simplest form of information (natural text) and ending with more complex type of
classical ciphers (periodic polyalphabetic system and polygraph system with four degrees of key order). The aim of this paper
is to prove that all classical ciphers can be classified or identified depending on the degree of complexity of the ciphertext. This
can be done by using three levels of classification. The obtained results showed that the proposed classifier can successfully
classify the classical cipher systems. This is a clear success for the proposed classifier opening further research directions and
can produce informative insights on the problem of identifying and classification of ciphertext produced by modern ciphers,
which is an important activity in automated cryptanalysis.