Over the last few decades, different mediums of secure communication use chaos which is demonstrated by some nonlinear dynamical systems. Chaos shows unpredictable behavior and this characteristic is quite helpful in different encryption techniques and for multimedia security. In this work, the chaotic behavior of the improved Tent-Sine map is conferred and ultimately a new method to construct substitution-boxes is proposed. This new method explores the features of chaos through TSS map and algebraic Mobius transformation to generate strong S-boxes. The S-boxes are assessed using standard tests suit which includes nonlinearity, strict avalanche criterion, bit independence criterion, linear approximation probability and differential uniformity. Moreover, the proposed S-boxes show excellent statistical properties under majority logic criterions such as correlation, homogeneity, energy, entropy, contrast. The statistical encryption results are demonstrate the better performance of the proposed S-boxes when compared with some of state of the art S-boxes including AES, Gray, APA S8 AES, Skipjack and validate the suitability of anticipated method.

In this paper, a novel method is being proposed to construct substitution box or boolean function for block ciphers using Gaussian distribution and linear fractional transform. The substitution box is constructed by employing a linear fractional transform based on box-muller transform, polarization decision and central limit algorithm. Cryptographic strength of the proposed S-boxes is evaluated with standard tests such as linear approximation probability, unified averaged changed intensity, bit independent criterion, histogram analysis, nonlinearity score, strict avalanche criterion and differential approximation probability. Results show that the proposed substitution box achieves better cryptographic strength as compared to state of the art techniques.

Massive advances in internet infrastructure are impacting e-healthcare services compared to conventional means. Therefore, extra care and protection is needed for extremely confidential patient medical records. With this intention, we have proposed an enhanced image steganography method, to improve imperceptibility and data hiding capacity of stego images. The proposed Image Region Decomposition (IRD) method, embeds more secret information with better imperceptibility, in patient's medical images. The algorithm decomposes the grayscale magnetic resonance imaging (MRI) images into three unique regions: low-intensity, medium-intensity, and high-intensity. Each region is made up of k number of pixels, and in each pixel we operate the block of n least significant bits (LSBs), where 1 ≤ n ≤ 3. Four classes of MRI images of different dimensions are used for embedding. Data with different volumes are used to test the images for imperceptibility and verified with quality factors. The proposed IRD algorithm is tested for performance, on the set of brain MRI images using peak signal-to-noise ratio (PSNR), mean square error (MSE) and structural similarity (SSIM) index. The results elucidated that the MRI stego image is imperceptible, like the original cover image by adjusting 2 nd and 1 st LSBs in the low-intensity region. Our proposed steganography technique provides a better average PSNR (49.27), than other similar methods. The empirical results show that the proposed IRD algorithm, significantly improves the imperceptibility and data embedding capacity, compared to the existing state-of-the-art methods.

This paper presents a real-time video-based pointing method that allows the sketching and writing of English text over air in front of a mobile camera. The proposed method has two main tasks. First, it tracks the colored fingertip in the video frames and then applies English optical character reorganization over the plotted images to recognize the written characters. Moreover, the proposed method provides a natural human–system interaction without requiring a keypad, stylus, pen, glove, or any other device for character inputs. For the experiments, an application was developed using OpenCv with the JAVA language. The proposed method was tested on a Samsung Galaxy3 android mobile phone. The proposed algorithm showed an average accuracy rate of 92.083% when tested for different shaped alphabets. Here, more than 3000 different shaped characters were used. The proposed system is a software-based approach and is relevantly very simple, fast, and easy to use. It does not require sensors or any hardware other than a camera and red tape, and is applicable to all disconnected languages. It has one issue, though it is color-sensitive in that the existence of any red-colored object in the background before the start of and during the character writing can lead to false results.

Substitution permutation network (SP-Network) is a chain of linked mathematical primitives used in block cipher algorithms. Proposed novel design of cryptographic SP-Network consists of three cryptographic primitives; substitution box permutation box, and random key sequences, including one key whitening operation. A new design is being proposed for each cryptographic primitive. Cryptographic strength of the proposed SP-Network is evaluated by employing various standard tests; strict avalanche criterion, differential approximation probability, bit independent criterion, linear approximation probability, nonlinearity test, unified averaged changed intensity, histogram analysis and coefficient correlation tests. The outcomes of the investigations validate that the designed cryptosystem is stable for secure communication and attains better cryptographic strength as compared to other state of the art techniques.

Block ciphers are widely used for securing data and are known for their resistance to various types of attacks. The strength of a block cipher against these attacks often depends on the S-boxes used in the cipher. There are many chaotic map-based techniques in the literature for constructing the dynamic S-Boxes. While chaos-based approaches have certain attractive properties for this purpose, they also have some inherent weaknesses, including finite precision effect, dynamical degradation of chaotic systems, non-uniform distribution, discontinuity in chaotic sequences. These weaknesses can limit the effectiveness of chaotic map-based substitution boxes. In this paper, we propose an innovative approach for constructing dynamic S-boxes using Gaussian distribution-based pseudo-random sequences. The proposed technique overcomes the weaknesses of existing chaos-based S-box techniques by leveraging the strength of pseudo-randomness sequences. However, one of the main drawbacks of using Gaussian distribution-based pseudo-random sequences is the low nonlinearity of the resulting S-boxes. To address this limitation, we introduce the use of genetic algorithms (GA) to optimize the nonlinearity of Gaussian distribution-based S-boxes while preserving a high level of randomness. The proposed technique is evaluated using standard S-box performance criteria, including nonlinearity, bit independence criterion (BIC), linear approximation probability (LP), strict avalanche criterion (SAC), and differential approximation probability (DP). Results demonstrate that the proposed technique achieves a maximum nonlinearity of 112, which is comparable to the ASE algorithm.