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An image encryption algorithm based on chaotic system and compressive sensing

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TLDR
An image encryption algorithm based on chaotic system and compressive sensing and the ECA that can compress and encrypt the image simultaneously by use of CS, which may reduce the amount of data and storage space.
About: 
This article is published in Signal Processing.The article was published on 2018-07-01. It has received 275 citations till now. The article focuses on the topics: Encryption & Chaotic.

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Citations
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Journal ArticleDOI

Image encryption algorithm based on the matrix semi-tensor product with a compound secret key produced by a Boolean network

TL;DR: Compared with other encryption algorithms, the algorithm proposed in this paper is more secure and effective, and it is also suitable for color image encryption.
Journal ArticleDOI

A fast image encryption algorithm based on compressive sensing and hyperchaotic map

TL;DR: Simulation and performance analysis verify that the new 2D-SLIM modulation map based on the improved two-dimensional closed-loop modulation coupling model has acceptable compression, high security and low time complexity.
Journal ArticleDOI

An efficient visually meaningful image compression and encryption scheme based on compressive sensing and dynamic LSB embedding

TL;DR: An efficient visually meaningful image compression and encryption (VMICE) scheme is proposed by combining compressive sensing (CS) and Least Significant Bit (LSB) embedding, robust to known-plain text and chosen-plaintext attacks.
Journal ArticleDOI

Colour image encryption algorithm combining Arnold map, DNA sequence operation, and a Mandelbrot set

TL;DR: Simulation and security analysis confirm that the proposed image encryption scheme demonstrates extraordinary performance in terms of security.
Journal ArticleDOI

Color image compression and encryption scheme based on compressive sensing and double random encryption strategy

TL;DR: A 4-D hyperchaotic system is applied to produce chaotic sequences for confusion and diffusion, such that the proposed image cryptosystem may withstand known-plaintext and chosen-plain Text attacks.
References
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Compressed sensing

TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Journal ArticleDOI

Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

TL;DR: In this paper, the authors considered the model problem of reconstructing an object from incomplete frequency samples and showed that with probability at least 1-O(N/sup -M/), f can be reconstructed exactly as the solution to the lscr/sub 1/ minimization problem.
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Some basic cryptographic requirements for chaos-based cryptosystems

TL;DR: The suggested guidelines address three main issues: implementation, key management and security analysis, aiming at assisting designers of new cryptosystems to present their work in a more systematic and rigorous way to fulfill some basic cryptographic requirements.
Proceedings Article

Compressive sensing

TL;DR: This paper overviews the recent work on compressive sensing, a new approach to data acquisition in which analog signals are digitized for processing not via uniform sampling but via measurements using more general, even random, test functions.
Journal ArticleDOI

Cryptographic requirements for chaotic secure communications

TL;DR: In this paper, the authors provide a set of guidelines that new cryptosystems would benefit from adhering to, such as correct key management and security analysis, and some practical aspects of communications such as channel noise, limited bandwith, and attenuation.
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