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Journal of Discrete Mathematical Sciences and Cryptography cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

Cryptanalysis of ciphers using machine learning

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pp. 769–777Vol. 29Issue 2-BFebruary 2026DOI: 10.47974/JDMSC-2527 Crossmark XML
Received:
07 May 2025
Published Online:
18 Feb 2026
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-2527
Pages:
769–777

Abstract

This paper focuses on the recognition of cipher encryption keys via machine learning, specifically Vigenère and Advanced Encryption Standard (AES) ciphers. It does this by analyzing pairs of plaintexts with their associated ciphertexts. It is a study that attempts to achieve a classification model for the task of predicting the encryption key between pairs of plaintexts and ciphertext without knowledge of the encryption key. A set of different plaintexts, ciphertext, and keys have been used to train the model. The results had proved the success of machine learning over existing encryption techniques, also illuminating their potential weaknesses and further giving impetus to the field of cryptanalysis. 

Keywords

Subject Classifications

Primary 94A60Secondary 68T05

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