TY  - JOUR
T1  - Classification and Identification of Classical Cipher Type using Artificial Neural Networks
AU - Abd, Ahmed J. AU - Al-Janabi, Sufyan T. Faraj 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 11
SP  - 3549
EP  - 3556
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.3549.3556
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.3549.3556
KW  - Artificial Neural Networks (ANNs)
KW  -classical ciphers
KW  -classification
KW  -polyalphabetic system
KW  -polygraph system informative insights
KW  -complexity
KW  -ciphertext
AB  - In this study, the capability of classifying the main types of classical ciphers systems is presented
using Artificial Neural Networks (ANNs) starting from simplest form of information (natural text) and ending
with more complex type of classical ciphers (periodic polyalphabetic system and polygraph system with 4
degree of key order). The aim of this study 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 3 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.
ER  -