Error function attack of chaos synchronization based encryption schemes

Using a reservoir computer to learn chaotic attractors, with applications to chaos synchronization and cryptography

Using the machine learning approach known as reservoir computing, it is possible to train one dynamical system to emulate another. We show that such trained reservoir computers reproduce the properties of the attractor of the chaotic system sufficiently well to exhibit chaos synchronization. That is, the trained reservoir computer, weakly driven by the chaotic system, will synchronize with the chaotic system. Conversely, the chaotic system, weakly driven by a trained reservoir computer, will synchronize with the reservoir computer. We illustrate this behavior on the Mackey-Glass and Lorenz systems. We then show that trained reservoir computers can be used to crack chaos based cryptography and illustrate this on a chaos cryptosystem based on the Mackey-Glass system. We conclude by discussing why reservoir computers are so good at emulating chaotic systems.

On the security of a spatiotemporal chaotic cryptosystem

Recently, Tang et al. [Phys Lett. A 318, 388 (2003)] proposed a spatiotemporal cryptosystem based on one-way coupled map lattices. They claim that it has high security, fast encryption speed, and short synchronization transient. This work proves that this scheme has some security weaknesses. Indeed, we propose an attack which the system cannot withstand.

Hash function based on chaotic map lattices

A new hash function system, based on coupled chaotic map dynamics, is suggested. By combining floating point computation of chaos and some simple algebraic operations, the system reaches very high bit confusion and diffusion rates, and this enables the system to have desired statistical properties and strong collision resistance. The chaos-based hash function has its advantages for high security and fast performance, and it serves as one of the most highly competitive candidates for practical applications of hash function for software realization and secure information communications in computer networks.

Selective image encryption using a spatiotemporal chaotic system

A universal selective image encryption algorithm, in which the spatiotemporal chaotic system is utilized, is proposed to encrypt gray-level images. In order to resolve the tradeoff between security and performance, the effectiveness of selective encryption is discussed based on simulation results. The scheme is then extended to encrypt RGB color images. Security analyses for both scenarios show that the proposed schemes achieve high security and efficiency.

Public-key encryption based on generalized synchronization of coupled map lattices

Currently used public-key cryptosystems are based on difficulties in solving certain numeric theoretic problems, in which the way to predict the private key from the knowledge of the public key is computationally infeasible. Here we propose a method of constructing public-key cryptosystems by generalized synchronization of coupled map lattices, in which the difficulty in predicting the synchronous function is used as the trap-door function to deduce the private key from the public key. In specific, we implement this idea on the method of "Merkle's puzzles," and find that, incorporated with the chaotic dynamics, this traditional method is equipped with some new features and can be practical in certain situations.