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A Novel Encryption Algorithm Using Chaotic Lorenz Attractor and Knights Tour

Published: 25 September 2015 Publication History

Abstract

A considerable amount of research has been carried out in harvesting the benefit of chaos theory in image encryption. However, there are not many schema that effectively maximize the advantages of Lorenz system. In this paper, we present one such image encryption algorithm that utilizes the Lorenz system for pixel manipulations. The schema employs a unique diffusion technique using Knight's tour and ensures a secure encryption with high key sensitivity. Various security checks such as histogram analysis, information entropy analysis and correlation analysis were carried out on the encrypted image. Simulation results prove that the algorithm gives excellent encryption parameters like information entropy and correlation coefficients along with the encrypted image being secure against commonly known attacks. The paper also compares the algorithm with other similar encryption methods.

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ICCCT '15: Proceedings of the Sixth International Conference on Computer and Communication Technology 2015
September 2015
481 pages
ISBN:9781450335522
DOI:10.1145/2818567
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 September 2015

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Author Tags

  1. Chaotic System
  2. Color image encryption
  3. Knight's Tour
  4. Lorenz attractor

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ICCCT '15

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Overall Acceptance Rate 33 of 124 submissions, 27%

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