A novel hyper-chaotic image encryption with sparse-representation based compression
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A novel hyper-chaotic image encryption with sparse-representation based compression J Karmakar 1 & D Nandi 2 & M K Mandal 1 Received: 24 April 2019 / Revised: 18 March 2020 / Accepted: 27 May 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract
This digital era uses lots of images in communication, which are confidential and large in volume. The transmission channel thus arises the question of security as well as transmission load. To date, several works are there to solve this issue. However, they fail to provide a single unit that gives these two facilities in a unified way. This paper presents a novel technique of unification of image compression and encryption in a single module via sparse-representation of image frames and hyper-chaotic encryption techniques. In this work, we have proposed a method to estimates the sparse vectors of a given image using a regularized trained over-complete dictionary and encrypt the non-zero coefficients of the sparse vectors using key-streams generated by a hyper-chaotic system. This sparse coding based encryption technique provides a higher compression ratio (CR) compared to some recently proposed techniques on one side and increases security level on the other side. Moreover, the security is strengthened by using this key-sequence in different steps in the encryption scheme. Thus the compressed-encrypted outputs are stronger than simple chaotic encryption against any intruder. The efficiency and authenticity of the proposed algorithm are verified through several quality-index e.g. entropy, CR, etc. The resistivity of the proposed algorithm toward the known or chosen-plaintext attack is also analyzed. The results of the key sensitivity test, and cropping attack test also ensure the authors’ claim. The comparison of the proposed technique with some recently published works justifies the reliability of this work. Keywords Dictionary learning. Sparse-representation. Run-length encoding. Image compression. Hyper-chaotic system. Image encryption
* M K Mandal [email protected]
1
Department of Physics, National Institute of Technology, Durgapur 713209, India
2
Department of Computer Science and Engineering, National Institute of Technology, Durgapur 713209, India
Multimedia Tools and Applications
1 Introduction Nowadays, every communication system is being connected to the internet. It is reported that the Internet of Things (IoT) network will consist of almost 50 billion objects by 2020 [21] and IoT will make a huge impact on business functionality very soon. The rapid increase of the use of video and images in various fields of science, technology, medical, defense, and social media is evoking the requirement of a secured and fast transmission as well as less storage for storing the image and video documents. To meet these requirements we have to face the following problems: (1) for transmission with good speed we need large bandwidth in the communication channel, (2) a large amount of data like image and video takes a long
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