DocumentCode
2813667
Title
Cloud authentication based on encryption of digital image using edge detection
Author
Yassin, Ali A. ; Hussain, Abdullah A. ; Mutlaq, Keyan Abdul-Aziz
Author_Institution
Comput. Sci. Dept., Basra Univ., Basra, Iraq
fYear
2015
fDate
3-5 March 2015
Firstpage
1
Lastpage
6
Abstract
The security of cloud computing is the most important concerns that may delay its well-known adoption. Authentication is the central part of cloud security, targeting to gain valid users for accessing to stored data in cloud computing. There are several authentication schemes that based on username/password, but they are considered weak methods of cloud authentication. In the other side, image´s digitization becomes highly vulnerable to malicious attacks over cloud computing. Our proposed scheme focuses on two-factor authentication that used image partial encryption to overcome above aforementioned issues and drawbacks of authentication schemes. Additionally, we use a fast partial image encryption scheme using Canny´s edge detection with symmetric encryption is done as a second factor. In this scheme, the edge pixels of image are encrypted using the stream cipher as it holds most of the image´s data and then we applied this way to authenticate valid users. The results of security analysis and experimental results view that our work supports a good balance between security and performance for image encryption in cloud computing environment.
Keywords
cloud computing; cryptography; edge detection; Canny edge detection; cloud authentication; cloud computing security; digital image partial encryption; image digitization; stream cipher; symmetric encryption; two-factor authentication; Authentication; Cloud computing; Digital images; Encryption; Image edge detection; Authentication; Cloud Computing; Edge Detection; Image encryption; Password; Service Provider;
fLanguage
English
Publisher
ieee
Conference_Titel
Artificial Intelligence and Signal Processing (AISP), 2015 International Symposium on
Conference_Location
Mashhad
Print_ISBN
978-1-4799-8817-4
Type
conf
DOI
10.1109/AISP.2015.7123517
Filename
7123517
Link To Document