Keyspace

Abstract: Today’s technological era, the booming desire for e-healthcare has inflated the attention towards the security of data from cyber attacks. As the digital medical images are transferred over the public network, there is a demand to shield an adequate level of protection. One of the prominent techniques is encryption which secures the medical images. This paper recommends a DICOM image encryption based upon chaotic attractors on frequency domain by integer wavelet transform (IWT) and fused with deoxyribonucleic acid (DNA) sequence on the spatial domain. The proposed algorithm uses a chaotic 3D Lorenz attractor and logistic map to generate pseudo-random keys for encryption. The algorithm involves subsequent stages, i.e. permutation, substitution, encoding, complementary and decoding. To endorse the resistance of the proposed algorithm, various analyses have been examined for 256 × 256 DICOM images by achieving an average entropy of 7.99, larger keyspace of 10238 and non-zero correlation. The overall results confirm that the proposed algorithm is robust against the brute force attacks.

Abstract: In its most general form, the Hill cipher's keyspace consists of all matrices of a given dimension that are invertible over ${{\open Z}_m} . Working from known results over finite fields, we assemble and prove a formula for the number of such matrices. We also compare this result with the total number of matrices and the number of involutory matrices for a given dimension and modulus, identifying the effects of change in dimension and modulus on the order of the keyspace.

Abstract: In the age of Information Technology, the day-life required transmitting millions of images between users. Securing these images is essential. Digital image encryption is a well-known technique used in securing image content. In image encryption techniques, digital images are converted into noise images using secret keys, where restoring them to their originals required the same keys. Most image encryption techniques depend on two steps: confusion and diffusion. In this work, a new algorithm presented for image encryption using a hyperchaotic system and Fibonacci Q-matrix. The original image is confused in this algorithm, utilizing randomly generated numbers by the six-dimension hyperchaotic system. Then, the permutated image diffused using the Fibonacci Q-matrix. The proposed image encryption algorithm tested using noise and data cut attacks, histograms, keyspace, and sensitivity. Moreover, the proposed algorithm’s performance compared with several existing algorithms using entropy, correlation coefficients, and robustness against attack. The proposed algorithm achieved an excellent security level and outperformed the existing image encryption algorithms.

Abstract: In this growing era, a massive amount of digital electronic health records (EHRs) are transferred through the open network. EHRs are at risk of a myriad of security threats, to overcome such threats, encryption is a reliable technique to secure data. This paper addresses an encryption algorithm based on integer wavelet transform (IWT) blended with deoxyribo nucleic acid (DNA) and chaos to secure the digital medical images. The proposed work comprises of two phases, i.e. a two-stage shuffling phase and diffusion phase. The first stage of shuffling starts with initial block confusion followed by row and column shuffling of pixels as the second stage. The pixels of the shuffled image are circularly shifted bitwise at the first stage of diffusion to enhance the security of the system against differential attack. The second stage of diffusion operation is based on DNA coding and DNA XOR operations. The experimental analyses have been carried out with 100 DICOM test images of 16-bit depth to evaluate the strength of the algorithm against statistical and differential attacks. By the results, the maximum entropy has been obtained an average of 15.79, NPCR of 99.99, UACI of 33.31, and larger keyspace of 10140, which infer that our technique overwhelms various other state-of-the-art techniques.