An Image Encryption Algorithm Based on High-dimensional Chaotic Systems

被引:0
|
作者
Tang Qi [1 ]
Jiang Jun-min [1 ]
Jiang Jun-li [1 ]
机构
[1] Xian Univ Posts & Telecommun, Xian, Peoples R China
来源
2016 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (ICSPCC) | 2016年
关键词
color image encryption; information entropy; correlation; combination chaos; KEYS;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In the field of image encryption, chaotic system is more and more used in the design of secure communication system because of its characteristics of similar noise and high sensitivity to the initial value. Image encryption methods based on high-dimensional chaotic has become research hotspots, and the development of combination chaos has become development trend of image encryption. The high dimensional chaotic parameters can effectively improve the key space of the encryption method, but the nonlinear behavior of high dimensional chaos if more difficult to predict than low dimensional chaos. The combination chaos which combined some different chaotic systems is sensitive to the initial value and has anti-analysis capabilities. Combination of some high dimensional chaotic maps in the encryption system can improve which performance significantly. A color image encryption algorithm based on high-dimensional chaotic system has been proposed in this paper, which combined two high-dimensional chaotic systems to form a more complex chaotic system, also used one-time key stream sequences to enhance information entropy of the encrypted image and reduce the correlation between the adjacent pixels, and the key sequence was generated by the Hyperhenon system, and the initial value of Hyperhenon system derived from the Hash values related to the plain image, those ensured the algorithm confidentiality and stability. Theoretical analysis and experimental results from key space analysis encrypted performance of each element, information entropy analysis, and robustness against noise show that the proposed algorithm has a lower adjacent pixels, higher information entropy and anti-noise performance.
引用
收藏
页数:4
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