Proceedings of the 2016 4th International Conference on Sensors, Mechatronics and Automation (ICSMA 2016)

Digital Image Multiple Encryption Algorithm based on Compressive Sensing

Authors
Zhan Yu, Changlun Zhang, Hengyou Wang, Nan Ning
Corresponding Author
Zhan Yu
Available Online December 2016.
DOI
10.2991/icsma-16.2016.114How to use a DOI?
Keywords
Image Encryption; Compressive Sensing; Arnold Transform; Logistic Map
Abstract

We propose a new method for the efficiency and the security of digital image transmission, termed digital image multiple encryption algorithm based on compressive sensing. Compressive sensing is utilized to compress and encrypt a digital image with the random measurement matrix as key, Arnold transform and Logistic map are used to encrypt the image again to realize the multiple encryption of image. The experimental results show that the encryption algorithm has such features as high key sensitivity, low data volume and can resistance some common attack.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Sensors, Mechatronics and Automation (ICSMA 2016)
Series
Advances in Intelligent Systems Research
Publication Date
December 2016
ISBN
10.2991/icsma-16.2016.114
ISSN
1951-6851
DOI
10.2991/icsma-16.2016.114How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhan Yu
AU  - Changlun Zhang
AU  - Hengyou Wang
AU  - Nan Ning
PY  - 2016/12
DA  - 2016/12
TI  - Digital Image Multiple Encryption Algorithm based on Compressive Sensing
BT  - Proceedings of the 2016 4th International Conference on Sensors, Mechatronics and Automation (ICSMA 2016)
PB  - Atlantis Press
SP  - 657
EP  - 661
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsma-16.2016.114
DO  - 10.2991/icsma-16.2016.114
ID  - Yu2016/12
ER  -