In order to improve the color in the process of image transmission security and efficiency, sine chaos mapping and Hopfield neural network model is put forward with the combination of image encryption algorithm. Firstly, sinusoidal chaotic mapping is adopted in the image scrambling stage to reduce the high correlation between image pixels; secondly, the key flow generated by iterative Hopfield chaotic neural network is used to complete the image diffusion; then, the image encryption is completed through bit operation; finally, the effectiveness and security of the encryption algorithm are analyzed. It is shown from that result and statistical analysis of the simulation that the algorithm has a variety of anti-attack ability and has high safety performance.
The image encryption algorithm based on chaotic system has been widely used at present. For this kind of algorithm, the encryption mechanism of "scrambling - diffusion" and multiple iterations are mainly adopted. In this paper, the common one-dimensional logistic chaotic mapping is taken as an example to analyze the influence of "scrambling - diffusion" and the number of iterations on the encryption effect. The simulation results show that, when only the chaotic system is used to complete the encryption operation, except for the key space, the contribution of "scrambling - diffusion" and single diffusion operation to the image encryption effect is basically the same, and the number of iterations has no significant effect on the encryption. When a "scrambling - diffusion" mechanism and multiple iterations are employed, the encryption effect may be enhanced by combining other cryptographic operations.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.