Image Encryption using Chaos-Driven Elliptic Curve Pseudo-random Number Generators

Omar Reyad , Zbigniew Kotulski , W. M. Abd-Elhafiez


Pseudo-random number sequences which using the form of elliptic curves can be generated efficiently in software or hardware by the same methods that are used for the implementation of elliptic curve (EC) public-key cryptosystems. In this paper, we proposed a secure image encryption scheme using key sequences generated from Chaos-Driven Elliptic Curve Pseudo-random Number Generator (C-D ECPRNG). This key sequences derived from random sequences based on EC points operations driven by a chaotic map. These constructions improve randomness properties of the generated sequences since it combines good statistical properties of an ECPRNG and a Chaotic Pseudo-random Number Generator (CPRNG). Entropy analysis of two test images shows that randomness of the ciphered images with the proposed key schemes are more random than in case of the ECPRNG without modulation by a chaotic map. Statistical and differential analysis demonstrate that the proposed schemes have adequate security for the confidentiality of digital images and the encryption is efficient compared to other competitive algorithms.
Author Omar Reyad IT
Omar Reyad,,
- The Institute of Telecommunications
, Zbigniew Kotulski IT
Zbigniew Kotulski,,
- The Institute of Telecommunications
, W. M. Abd-Elhafiez - [Sohag University (NBE)]
W. M. Abd-Elhafiez,,
- Sohag University
Journal seriesApplied Mathematics & Information Sciences, ISSN 2325-0399 [1935-0090]
Issue year2016
Publication size in sheets0.5
Keywords in EnglishElliptic Curve Cryptography, Random Number Generator, Image Encryption, Chaotic Maps
projectThe Develpment of Digital Communicatios. Project leader: Siuzdak Jerzy, , Phone: +48 22 234-7232, start date 27-04-2015, end date 31-12-2016, IT/2015/statut, Completed
WEiTI Działalność statutowa
Languageen angielski
2016 Reyad Kotulski Image Enctryption.pdf 1,015.65 KB
Score (nominal)30
ScoreMinisterial score = 0.0, 27-03-2017, ArticleFromJournal
Ministerial score (2013-2016) = 30.0, 27-03-2017, ArticleFromJournal
Citation count*2 (2018-06-21)
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