DocumentCode
2213822
Title
A Chaotic Images Encryption Algorithm with the Key Mixing Proportion Factor
Author
Enzeng, Dong ; Zengqiang, Chen ; Zhuzhi, Yuan ; Zaiping, Chen
Author_Institution
Dept. of Autom., Tianjin Univ. of Technol., Tianjin
Volume
1
fYear
2008
fDate
19-21 Dec. 2008
Firstpage
169
Lastpage
174
Abstract
The pseudo random property of chaotic sequences is very useful in the field of information security, based on the idea of orbit hopping, a chaotic image encryption algorithm with a key mixing proportion factor is proposed. In the proposed algorithm the position scrambling matrix and the value scrambling matrix are generated by the improved chaotic logistic sequences. A key mixing proportion factor (KMPF) is generated based on the plaintext information. By adding this factor, most of cipher text elements value can be changed by the change of any plaintext element. The Security of the proposed algorithm is improved with this factor, and the ability of the proposed algorithm resisting plaintext attacks is strengthened obviously, and the encryption algorithm can resist the statistical and differential attacks effectively, moreover, the algorithm has a large key space and high encryption speed. The effectiveness of the proposed algorithm is verified by the theoretical analysis and numerical simulations.
Keywords
cryptography; image processing; numerical analysis; security of data; chaotic images encryption algorithm; encryption algorithm; information security; numerical simulations; plaintext information; position scrambling matrix; value scrambling matrix; Algorithm design and analysis; Automation; Chaos; Cryptography; Equations; Information security; Logistics; Numerical simulation; Probability distribution; Resists;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Management, Innovation Management and Industrial Engineering, 2008. ICIII '08. International Conference on
Conference_Location
Taipei
Print_ISBN
978-0-7695-3435-0
Type
conf
DOI
10.1109/ICIII.2008.25
Filename
4737520
Link To Document