Development of Efficient Color Image Encryption Techniques Using Evolutionary Approaches

Abstract

The advancements in multimedia applications are rapidly increasing nowadays. A number of confidential images are transferred over the public networks day-by-day. Therefore, secure transmission of images has become a significant research area. Several image encryption techniques have been designed to achieve the particular necessities raised by different users. The image encryption techniques convert confidential image into a noisy image using secret key. The actual image is recovered if and only if the receiver has an authenticated secret key. Various techniques such as chaotic maps, evolutionary, DNA, cellular automata, etc. have been used to encrypt the images. Image encryption differs from text encryption as a result of few numbers of inherent characteristics such as huge size and redundancy. The traditional text encryption techniques fail to handle huge size and redundancy of images. The main challenges of image encryption are robustness against attacks, keyspace, key sensitivity, and diffusion. The chaotic maps are extensively utilized in the field of image encryption to generate the secret keys. However, these maps suffer from parameter tuning problem. Recent studies have shown that the improper selection of parameter values makes secret keys generated from chaotic system vulnerable. Therefore, many meta-heuristic techniques have been introduced in the literature for image encryption to improve the selection of chaotic system s parameters. However, these techniques suffer from poor computational speed. Also, designing an efficient multi-objective fitness function is still a challenging issue. To overcome these issues, meta-heuristic based image encryption techniques are proposed in this thesis. An efficient image encryption technique in nonsubsampled contourlet transform using genetic algorithm (IGN) is proposed. Initially, nonsubsampled contourlet transform is utilized to decompose the input image into sub-bands. The beta chaotic map is used to develop a pseudo-random key that encrypts the c