Chaos-based authentication of encrypted images under MQTT for IoT protocol

Abstract

In lightweight cryptographic applications, the authentication of encrypted data is a challenge that can be solved by using high-order chaotic systems. The proposed work shows that increasing the length of bits in a Hash function, leads to diminish the possibility of a collision. Using high-order chaotic systems, can also lead to use large prime numbers by exploiting the fact that the division and modulo operations provide a better distribution in a most uniform way. In addition, because a prime number has factors including 1 and himself, then this greatly reduces the appearance of repetitive patterns in a modulo operation. In this manner, this article presents the implementation of a chaos based system for authentication of encrypted RGB images using Raspberry Pi devices. First, a two dimensional (2D) map, and 3D, and 4D chaotic systems, are implemented on Raspberry Pi devices to design pseudo-random number generators (PRNG). Second, the randomness of the sequences is evaluated by performing NIST (National Institute of Standards and Technology) tests. Third, the random sequences are used to construct a stream cipher and an authenticated Hash function based on a method called pseudo dot product. Fourth, RGB images are encrypted using the PRNGs based on 2D, 3D, and 4D chaotic systems. In the proposed work, all these processes are performed under a machine-to-machine (M2M) wireless connectivity system, which is available on the message queuing telemetry transport (MQTT) communication protocol for Internet of Things (IoT). In the experiments, three Raspberry Pi devices are configured as a publisher, a broker, and a subscriber to work on MQTT for sending and receiving encrypted RGB images, while the images are authenticated through the evaluation of Hash function tags, which are generated by using 2D, 3D, and 4D chaotic systems. The main conclusion is that the encryption/decryption and authentication processes are much better when using high-dimensional chaotic systems.