Applications of Artificial Intelligence to Cryptography

  • Jonathan Blackledge Stokes Professor, Science Foundation Ireland
  • Napo Mosola Research Associate, School of Mathematics, Statistics & Computer Science, University of KwaZulu-Natal, South Africa
Keywords: Artificial Intelligence, Artificial Neural Networks, Evolutionary Computing, Machine Learning.


This paper considers some recent advances in the field of Cryptography using Artificial Intelligence (AI) It specifically considers the applications of Machine Learning (ML) and Evolutionary Computing (EC) concepts used to generate ciphers. A short overview is given on Artificial Neural Networks (ANNs) and the principles of Deep Learning (DL) using Deep ANNs.  In this context, the paper considers: (i) the implementation of EC and ANNs to generate unique and unclonable ciphers; (ii) ML strategies for detecting the genuine randomness (or otherwise) of binary streams for applications in Cryptanalysis.  The paper aims to provide an overview on how AI can be applied for encrypting data and undertaking cryptanalysis of such data and other encrypted data classes in order to assess the cryptographic strength of an encryption algorithm. For example, to detect patterns of intercepted data streams that are signatures of encrypted data. An application is presented which includes authentication of high-value documents such as bank notes, using smartphones.  Using an antenna of a smartphone to read (in the near field) an embedded flexible integrate circuit with a non-programmable coprocessor, ultra-strong encrypted information can be used on-line for validation.


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How to Cite
Blackledge, J., & Mosola, N. (2020). Applications of Artificial Intelligence to Cryptography. Transactions on Machine Learning and Artificial Intelligence, 8(3), 21-60.