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NNSF of China [60076015]; key science project of Fujian Province, China [2009H0037]; science project of Xiamen City, China [3502Z20081073]

The security of the symmetric probabilistic encryption scheme based on chaotic attractors of neural networks is analyzed and discussed. Firstly, the key uniqueness is proved by analyzing the rotation transform matrix to avoid the attack of the equivalent key. Secondly, the distributed uniformity of the numbers “0” and “1” in the corresponding attracting domain for every chaotic attractor is analyzed by the statistics method. It is testified that the distributed uniformity can be kept if the synaptic matrix of the neural network is changed by a standard permutation matrix. Two annotations based on the results above are proposed to improve the application security of the encryption algorithm.

The proposed perceptual mask is based on the singularity of cover image and matches very well with the properties of the human visual system. The cover colour image is decomposed into several subbands by the wavelet transform. The watermark composed of chaotic sequence and the covert image is embedded into the subband with the largest energy. The chaos system plays an important role in the security invisibility and robustness of the proposed scheme. The parameter and initial state of chaos system can directly influence the generation of watermark information as a key. Moreover, the watermark information has the property of spread spectrum signal by chaotic sequence to improve the invisibility and security of watermarked image. Experimental results and comparisons with other watermarking techniques prove that the proposed algorithm is effective and feasible, and improves the security, invisibility and robustness of watermarking information.

We propose a data hidding technique in a stilt image. This technique is based on chaotic sequence in the transform domain of covert image. We use different chaotic random sequences multiplied by multiple sensitive images, respectively, to spread the spectrum of sensitive images. Multiple sensitive images are hidden in s covert image as a form of noise. The results of theoretical analysis and computer simulation show the new hiding technique have better properties with high security, imperceptibility and capacity for hidden information in comparison with the conventional scheme such as LSB (Least Significance Bit).

Based on chaotic maps, a novel robust watermarking algorithm is presented in this paper. The proposed approach improves the invisibility, robustness and security of traditional watermarking algorithm by using chaotic sequences. Taking advantage of the characteristics of extreme sensitivity to initial conditions, Chebyshev maps are used to generate substantially different watermarks as a key. This technique has been shown to offer an added security advantage over the more traditionally generated watermarks created from pseudorandom sequences, in that only the function seed needs to be stored. Various kinds of images are selected as watermark images in order to prove the fidelity of the proposed scheme. Simulation of the algorithm is performed on different types of images, and the results are compared with existing algorithms. Results show that the proposed scheme is simple and applicable, and can resist many attacks such as JPEG compression, rotation, cropping and noising.

A novel transform-domain image watermark based on chaotic sequences is proposed in this paper. A complex chaos-based scheme is developed to embed a gray-level image in the wavelet domain of the original color image signal. The chaos system plays an important role in the security and invisibility of the proposed scheme. The parameter and initial state of chaos system directly influence the generation of watermark information as a key. Meanwhile, the watermark information has the property of spread spectrum signal by chaotic sequence. To improve the invisibility of watermarked image Computer simulation results show that the proposed algorithm is imperceptible and is robust to most watermarking attacks, especially to image cropping, JPEG compression and multipliable noise.