"An Authenticated Trust and Reputation Calculation and Management System for Cloud and Sensor Networks Integration",
Information Forensics and Security, IEEE Transactions on,
Md Mizanur Rahman, S.;
"Investigation of security challenges and a novel security mechanism for cloud computing environment",
Web Applications and Networking (WSWAN), 2015 2nd World Symposium on,
"Privacy-preserving multimedia cloud computing via compressive sensing and sparse representation",
Information Security and Intelligence Control (ISIC), 2012 International Conference on,
In cloud computing communications, information security entails the protection of information elements (e.g., multimedia data), only authorized users are allowed to access the available contents. Fingerprint recognition is one of the popular and effective approaches for priori authorizing the users and protecting the information elements during the communications. However, traditional fingerprint recognition approaches have demerits of easy losing rich information and poor performances due to the complex inputs, such as image rotation, incomplete input image, poor quality image enrollment, and so on. In order to overcome these shortcomings, in this paper, a new fingerprint recognition scheme based on a set of assembled invariant moment (geometric moment and Zernike moment) features to ensure the secure communications is proposed. And the proposed scheme is also based on an effective preprocessing, the extraction of local and global features and a powerful classification tool, thus it is able to handle the various input conditions encountered in the cloud computing communication. The experimental results show that the proposed method has a higher matching accuracy comparing with traditional or individual feature based methods on public databases.