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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

ROI Image Encryption using YOLO and Chaotic Systems

Author 1: Sung Won Kang
Author 2: Un Sook Choi

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120754

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 7, 2021.

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Abstract: In this paper, we design a cellular automata (CA)-based ROI (region of interest) image encryption system that can effectively reduce computational cost and maintain an appropriate level of security. The proposed image encryption system obtains a cryptographic image through three steps. First, a region of interest with high importance is extracted from the entire image using deep learning. We use the YOLO (You Only Look Once) algorithm to extract the ROI from a given original image. Next, the detected ROI is encrypted using the Chen system, a chaotic-based function with high security. Finally, the execution time is effectively reduced by encrypting the entire image using a hardware-friendly CA. The safety of the proposed encryption system is verified through various statistical experiment results and analyses.

Keywords: Image encryption; cellular automata; YOLO algorithm; deep learning; Chen system; region of interest

Sung Won Kang and Un Sook Choi, “ROI Image Encryption using YOLO and Chaotic Systems” International Journal of Advanced Computer Science and Applications(IJACSA), 12(7), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120754

@article{Kang2021,
title = {ROI Image Encryption using YOLO and Chaotic Systems},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120754},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120754},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {7},
author = {Sung Won Kang and Un Sook Choi}
}


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