A robust image-based cryptology scheme based on cellular non-linear network and local image descriptors
Abstract
Cellular nonlinear network (CNN) provides an infrastructure for Cellular Automata to have not only an initial state but an input which has a local memory in each cell with much more complexity. This property has many applications which we have investigated it in proposing a robust cryptology scheme. This scheme consists of a cryptography and steganography sub-module in which a 3D CNN is designed to produce a chaotic map as the kernel of the system to preserve confidentiality and data integrity in cryptology. Our contributions are three-fold including (1) a feature descriptor is applied to the cover image to form the secret key while conventional methods use a predefined key, (2) a 3D CNN is used to make a chaotic map for making cipher from the visual message, and (3) the proposed CNN is also used to make a dynamic -LSB steganography. Conducted experiments on 25 standard images prove the effectiveness of the proposed cryptology scheme in terms of security, visual, and complexity analysis.
Cite
@article{arxiv.1808.03702,
title = {A robust image-based cryptology scheme based on cellular non-linear network and local image descriptors},
author = {Mohammad Mahdi Dehshibi and Jamshid Shanbehzadeh and Mir Mohsen Pedram},
journal= {arXiv preprint arXiv:1808.03702},
year = {2018}
}
Comments
This is an Accepted Manuscript of an article published by Taylor & Francis Group in the International Journal of Parallel, Emergent & Distributed Systems, available online: http://www.tandfonline.com/10.1080/17445760.2018.1510929