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Encryption of text file using a user controlled automatically-generated key

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conference contribution
posted on 2019-11-27, 09:36 authored by Halima Shnishah, David Mulvaney
Traditional symmetrical cryptographic algorithms generally provide an adequate degree of immunity to attacks aimed at revealing secret keys. A number of approaches exist for the automated generation of secret keys, but, for high security applications, some end users remain wary of approaches that are controlled by third parties. Consequently, there remains interest in certain high-security applications in being able to retain control over the method used for the generation of keys. In this paper, keys for both image encryption and decryption are obtained using the evolutionary computing tool Eureqa, in its modelling of pseudorandom input data. The secret keys generated by this approach and when applied to the encryption and decryption of gray-scale images are validated in a range of statistical tests, namely histogram, chisquare, correlation of adjacent pixel pairs, correlation between original and encrypted images, entropy and key sensitivity. Experimental results obtained from methods show that the proposed image encryption and decryption algorithms are secure and reliable, with the potential to be adapted to high-security image communication applications.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)

Pages

238 - 243

Source

IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publication date

2019-04-11

ISBN

9781538670019

Language

  • en

Location

Northumbria Univ London Campus, London, ENGLAND

Event dates

16th January 2019 - 18th January 2019

Depositor

Dr David Mulvaney . Deposit date: 26 November 2019