A Novel Chaotic Image Encryption using Generalized Threshold Function

In this paper, after reviewing the main points of image encryption and threshold function, we introduce the methods of chaotic image encryption based on pseudorandom bit padding that the bits be generated by the novel generalized threshold function (segmentation and self-similarity) methods. These methods decrease periodic effect of the ergodic dynamical systems in randomness of the chaotic image encryption. The essential idea of this paper is that given threshold functions of the ergodic dynamical systems. To evaluate the security of the cipher image of this scheme, the key space analysis, the correlation of two adjacent pixels and differential attack were performed. This scheme tries to improve the problem of failure of encryption such as small key space and level of security.Comment: 7 pages, 5 figures, Published in international Journal of Computer Applications (March 2012

Self-synchronizing stream ciphers and dynamical systems: state of the art and open issues

International audienceDynamical systems play a central role in the design of symmetric cryptosystems. Their use has been widely investigated both in ''chaos-based'' private communications and in stream ciphers over finite fields. In the former case, they get the form of automata named as Moore or Mealy machines. The main charateristic of stream ciphers lies in that they require synchronization of complex sequences generated by the dynamical systems involved at the transmitter and the receiver part. In this paper, we focus on a special class of symmetric ciphers, namely the Self-Synchronizing Stream Ciphers. Indeed, such ciphers have not been seriously explored so far although they get interesting properties of synchronization which could make them very appealing in practice. We review and compare different design approaches which have been proposed in the open literature and fully-specified algorithms are detailed for illustration purpose. Open issues related to the validation and the implementation of Self-Synchronizing Stream Ciphers are developped. We highlight the reason why some concepts borrowed from control theory appear to be useful to this end

Iot Based Alzheimer’s Disease Diagnosis Model for Providing Security Using Light Weight Hybrid Cryptography

Security in the Internet of things (IoT) is a broad yet active research area that focuses on securing the sensitive data being circulated in the network. The data involved in the IoT network comes from various organizations, hospitals, etc., that require a higher range of security from attacks and breaches. The common solution for security attacks is using traditional cryptographic algorithms that can protect the content through encryption and decryption operations. The existing solutions are suffering from major drawbacks, including computational complexities, time and space complexities, slower encryption, etc. Therefore, to overcome such drawbacks, this paper introduces an efficient light weight cryptographic mechanism to secure the images of Alzheimer’s disease (AD) being transmitted in the network. The mechanism involves major stages such as edge detection, key generation, encryption, and decryption. In the case of edge detection, the edge maps are detected using the Prewitt edge detection technique. Then the hybrid elliptic curve cryptography (HECC) algorithm is proposed to encrypt and secure the images being transmitted in the network. For encryption, the HECC algorithm combines blowfish with the elliptic curve algorithm to attain a higher range of security. Another significant advantage of the proposed method is selecting the ideal private key, which is achieved using the enhanced seagull optimization (ESO) algorithm. The proposed work has been tested in the Python tool, and the performance is evaluated with the Alzheimer’s dataset, and the outcomes proved its efficacy over the compared methods

A Simple and Robust Gray Image Encryption Scheme Using Chaotic Logistic Map and Artificial Neural Network

A robust gray image encryption scheme using chaotic logistic map and artificial neural network (ANN) is introduced. In the proposed method, an external secret key is used to derive the initial conditions for the logistic chaotic maps which are employed to generate weights and biases matrices of the multilayer perceptron (MLP). During the learning process with the backpropagation algorithm, ANN determines the weight matrix of the connections. The plain image is divided into four subimages which are used for the first diffusion stage. The subimages obtained previously are divided into the square subimage blocks. In the next stage, different initial conditions are employed to generate a key stream which will be used for permutation and diffusion of the subimage blocks. Some security analyses such as entropy analysis, statistical analysis, and key sensitivity analysis are given to demonstrate the key space of the proposed algorithm which is large enough to make brute force attacks infeasible. Computing validation using experimental data with several gray images has been carried out with detailed numerical analysis, in order to validate the high security of the proposed encryption scheme

A proposed lightweight image encryption using ChaCha with hyperchaotic maps

Image encryption plays a pivotal rule in enhancing telecommunications media. Since Privacy is necessary in our daily life in many areas, the personal image will be encrypted when it sent it over the Internet to the recipient to maintain privacy issue. In this paper, the image is encrypted using ChaCha symmetric stream cipher with Hyperchaotic Map. Due to the sensitivity characteristics of initial conditions, pseudo randomness chaotic maps and control parameters in chaotic, Hyperchaotic maps is use, higher security is obtained via using initial seed number, variance of parameters, and unpredictable direction of chaotic. The suggested lightweight image encryption has confirmed robustness contra brute force attacks by providing a massive key space. Furthermore, the suggested lightweight image encryption is eligible to defense from statistical cracking, insecurity of image based on criteria's histogram correlation and entropy