An efficient data masking for securing medical data using DNA encoding and chaotic system

Data security is utmost important for ubiquitous computing of medical/diagnostic data or images. Along with must consider preserving privacy of patients. Recently, deoxyribose nucleic acid (DNA) sequences and chaotic sequence are jointly used for building efficient data masking model. However, the state-of-art model are not robust against noise and cropping attack (CA). Since in existing model most digits of each pixel are not altered. This work present efficient data masking (EDM) method using chaos and DNA based encryption method for securing health care data. For overcoming research challenges effective bit scrambling method is required. Firstly, this work present an efficient bit scrambling using logistic sine map and pseudorandom sequence using chaotic system. Then, DNA substitution is performed among them to resist against differential attack (DA), statistical attack (SA) and CA. Experiment are conducted on standard considering diverse images. The outcome achieved shows proposed model efficient when compared to existing models

Research on digital image watermark encryption based on hyperchaos

The digital watermarking technique embeds meaningful information into one or more watermark images hidden in one image, in which it is known as a secret carrier. It is difficult for a hacker to extract or remove any hidden watermark from an image, and especially to crack so called digital watermark. The combination of digital watermarking technique and traditional image encryption technique is able to greatly improve anti-hacking capability, which suggests it is a good method for keeping the integrity of the original image. The research works contained in this thesis include: (1)A literature review the hyperchaotic watermarking technique is relatively more advantageous, and becomes the main subject in this programme. (2)The theoretical foundation of watermarking technologies, including the human visual system (HVS), the colour space transform, discrete wavelet transform (DWT), the main watermark embedding algorithms, and the mainstream methods for improving watermark robustness and for evaluating watermark embedding performance. (3) The devised hyperchaotic scrambling technique it has been applied to colour image watermark that helps to improve the image encryption and anti-cracking capabilities. The experiments in this research prove the robustness and some other advantages of the invented technique. This thesis focuses on combining the chaotic scrambling and wavelet watermark embedding to achieve a hyperchaotic digital watermark to encrypt digital products, with the human visual system (HVS) and other factors taken into account. This research is of significant importance and has industrial application value

Extended of TEA: A 256 bits block cipher algorithm for image encryption

This paper introduces an effective image encryption approach that merges a chaotic map and polynomial with a block cipher. According to this scheme, there are three levels of encryption. In the first level, pixel positions of the image are scuffled into blocks randomly based on a chaotic map. In the second level, the polynomials are constructed by taking N unused pixels from the permuted blocks as polynomial coefficients. Finally, the third level a proposed secret-key block cipher called extended of tiny encryption algorithm (ETEA) is used. The proposed ETEA algorithm increased the block size from 64-bit to 256-bit by using F-function in type three Feistel network design. The key schedule generation is very straightforward through admixture the entire major subjects in the identical manner for every round. The proposed ETEA algorithm is word-oriented, where wholly internal operations are executed on words of 32 bits. So, it is possible to efficiently implement the proposed algorithm on smart cards. The results of the experimental demonstration that the proposed encryption algorithm for all methods are efficient and have high security features through statistical analysis using histograms, correlation, entropy, randomness tests, and the avalanche effect