DocumentCode
2343687
Title
An Image Encryption Scheme Based on Cat Map and Hyperchaotic Lorenz System
Author
Jian Zhang
Author_Institution
Shenyang Fire Res. Inst., Shenyang, China
fYear
2015
fDate
13-14 Feb. 2015
Firstpage
78
Lastpage
82
Abstract
In recent years, chaos-based image cipher has been widely studied and a growing number of schemes based on permutation-diffusion architecture have been proposed. However, recent studies have indicated that those approaches based on low-dimensional chaotic maps/systems have the drawbacks of small key space and weak security. In this paper, a security improved image cipher which utilizes cat map and hyper chaotic Lorenz system is reported. Compared with ordinary chaotic systems, hyper chaotic systems have more complex dynamical behaviors and number of system variables, which demonstrate a greater potential for constructing a secure cryptosystem. In diffusion stage, a plaintext related key stream generation strategy is introduced, which further improves the security against known/chosen-plaintext attack. Extensive security analysis has been performed on the proposed scheme, including the most important ones like key space analysis, key sensitivity analysis and various statistical analyses, which has demonstrated the satisfactory security of the proposed scheme.
Keywords
cryptography; image processing; statistical analysis; cat map; chaos-based image cipher; complex dynamical behaviors; cryptosystem; hyperchaotic Lorenz system; image encryption scheme; key sensitivity analysis; key space analysis; key stream generation strategy; low-dimensional chaotic maps; permutation-diffusion architecture; security analysis; statistical analysis; Chaotic communication; Ciphers; Correlation; Encryption; cat map; hyperchaotic Lorenz system; image cipher; permutation-diffusion;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on
Conference_Location
Ghaziabad
Print_ISBN
978-1-4799-6022-4
Type
conf
DOI
10.1109/CICT.2015.134
Filename
7078671
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