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Chaos-based encryption may offer new quality in secure data transmission. A recently proposed Chaotic Key-Based Algorithm (CKBA) has been shown to be unavoidably susceptible to chosen/known plaintext attacks and ciphertextonly attacks. In this paper, Discrete wavelet transform and Modified Chaotic Key-Based Algorithm are proposed to enhance the security of CKBA. The enhanced security of the proposed algorithm is analyzed through cryptanalysis. Furthermore, Very large scale integration (VLSI) architecture of the proposed algorithm is designed. The VLSI architecture is implemented on an image using ModelSim to demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Illegal data access has become prevalent in wireless and general communication networks. Recently, the use of chaotic signals for secure data transmission has shown significant growth in developing chaotic encryption and decryption algorithms. The application of the Brahmagupta-Bhãskara (BB) equation for encryption is reported in a very recent article. However, a number of chaos-based algorithms are proved to be insecure in the literature. It is also shown in the literature that the BB equation based algorithm can be broken by a low complexity known plaintext attack. Hence, in this paper, a new secure cryptosystem based on the BB equation and chaos is proposed for image encryption and decryption. Cryptanalysis of the proposed cryptosystem is also provided. The efficacy of the proposed cryptosystem is illustrated through implementation results on two images. [ABSTRACT FROM AUTHOR]

Various switching-based median filters have been proposed in the literature for restoration of extremely corrupted images and video sequences by impulsive noise. Among these, switching median filters with boundary discriminative noise detection (BDND) are very effective and outperform all the previously proposed median-based filters. However, the calculation is very time-consuming. Hence, in this paper, a median filter with an efficient BDND (EBDND) is proposed for denoizing image and video sequences corrupted by impulsive noise. The proposed EBDND uses a faster sorting algorithm both in noise detection and adaptive filtering stages for the restoration of image and video sequences contaminated by impulse noise. For motion estimation of the video sequence, block-matching technique is used. The performance of the proposed EBDND is demonstrated through computer simulations in comparison with the BDND method. [ABSTRACT FROM AUTHOR]