Grayscale Image Authentication using Neural Hashing

Many different approaches for neural network based hash functions have been proposed. Statistical analysis must correlate security of them. This paper proposes novel neural hashing approach for gray scale image authentication. The suggested system is rapid, robust, useful and secure. Proposed hash function generates hash values using neural network one-way property and non-linear techniques. As a result security and performance analysis are performed and satisfying results are achieved. These features are dominant reasons for preferring against traditional ones.Comment: international journal of Natural and Engineering Sciences (NESciences.com) : Image Authentication, Cryptology, Hash Function, Statistical and Security Analysi

Performance Analysis of a Keyed Hash Function based on Discrete and Chaotic Proven Iterations

Security of information transmitted through the Internet is an international concern. This security is guaranteed by tools like hash functions. However, as security flaws have been recently identified in the current standard in this domain, new ways to hash digital media must be investigated. In this document an original keyed hash function is evaluated. It is based on chaotic iterations and thus possesses various topological properties as uniform repartition and sensibility to its initial condition. These properties make our hash function satisfy the requirements in this field. This claim is verified qualitatively and experimentally in this research work, among other things by realizing simulations of diffusion and confusion.Comment: Accepted the the Internet11 conferenc

One-Way Hash Function Based on Delay-Induced Hyperchaos

Peer reviewedPostprin

Analysis and Design Security Primitives Based on Chaotic Systems for eCommerce

Security is considered the most important requirement for the success of electronic commerce, which is built based on the security of hash functions, encryption algorithms and pseudorandom number generators. Chaotic systems and security algorithms have similar properties including sensitivity to any change or changes in the initial parameters, unpredictability, deterministic nature and random-like behaviour. Several security algorithms based on chaotic systems have been proposed; unfortunately some of them were found to be insecure and/or slow. In view of this, designing new secure and fast security algorithms based on chaotic systems which guarantee integrity, authentication and confidentiality is essential for electronic commerce development. In this thesis, we comprehensively explore the analysis and design of security primitives based on chaotic systems for electronic commerce: hash functions, encryption algorithms and pseudorandom number generators. Novel hash functions, encryption algorithms and pseudorandom number generators based on chaotic systems for electronic commerce are proposed. The securities of the proposed algorithms are analyzed based on some well-know statistical tests in this filed. In addition, a new one-dimensional triangle-chaotic map (TCM) with perfect chaotic behaviour is presented. We have compared the proposed chaos-based hash functions, block cipher and pseudorandom number generator with well-know algorithms. The comparison results show that the proposed algorithms are better than some other existing algorithms. Several analyses and computer simulations are performed on the proposed algorithms to verify their characteristics, confirming that these proposed algorithms satisfy the characteristics and conditions of security algorithms. The proposed algorithms in this thesis are high-potential for adoption in e-commerce applications and protocols

Enhanced Parallel Hash Function Algorithm Based on 3C Construction (EPHFA-3C)

The hash function is a function that can convert data from variable size to fixed-size data that can be used in security of communication like, authentication, digital signature and integration. In this paper, a parallel, secure and fast hash function algorithm that is based on 3C construction is proposed. It is an enhancement for the MD construction. This enhancement makes the construction more resistant to the extension and multi-blocks attacks. The parallel structure of the algorithm improves the speed of hashing and reduces the number of operations. The simulation analysis such as hashes distribution, confusion and diffusion properties, and collision resistance are executed. Based on the results, our proposed hash algorithm is efficient, simple, and has strong security compared with some recent hash algorithms

Building a Chaotic Proven Neural Network

International audienceChaotic neural networks have received a great deal of attention these last years. In this paper we establish a precise correspondence between the so-called chaotic iterations and a particular class of artificial neural networks: global recurrent multi-layer perceptrons. We show formally that it is possible to make these iterations behave chaotically, as defined by Devaney, and thus we obtain the first neural networks proven chaotic. Several neural networks with different architectures are trained to exhibit a chaotical behavior