Video Content Encryption as a Service and Performance Implications of Video Data Encryption on Cloud
T. Naga Raja1, V.V.Venkata Ramana2, A. Damodaram3
1T.Naga Raja*, Research Scholar JNTUH, Hyderabad, India
2Dr V.V.Venkata Ramana, Scientist-F, National Informatics Centre, Amaravati, India,
3Dr. A. Damodaram, Professor, SIT JNTUH, Hyderabad, India.
Manuscript received on October 18, 2019. | Revised Manuscript received on 26 October, 2019. | Manuscript published on November 10, 2019. | PP: 4718-4725 | Volume-9 Issue-1, November 2019. | Retrieval Number: A5044119119/2019©BEIESP | DOI: 10.35940/ijitee.A5044.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The immense growth in the video content retrieval and video content analysis have motivated the practitioners to migrate the video contents and the analytic applications on to the cloud. The cloud computing platform provides scalability for applications and data, which enables the application owners to deal with complex algorithms, which is needed for video content analysis and retrievals. The primary concern of the video data retrieval on cloud services are the weak security for the standard data during migrating from one VM to another VM. Also, the standard encryption algorithms have failed to demonstrate higher performance during encryption of a large file. Hence, the demand of the recent research is to ensure reduced performance implications for video content encryption over cloud services. This work proposes an adaptive encryption and decryption algorithm for large video data over cloud as Encryption as A Service (EAAS). This work proposes a novel key age calculation dependent on Quartic Polynomial Randomization. The quartic part utilized in the proposed calculation can produce numerous defining moments, which makes the calculation results hard to foresee and the utilization of polynomial randomization can further build the haphazardness of the defining moments. Likewise, the higher size of the video information must be diminished without rotting the data and without trading off the security. Subsequently, this work proposes a novel key edge comparability extraction procedure utilizing versatile movement. The similitude areas in the key casings contains comparable data and, in this manner, can be scrambled all around. This diminishes the time unpredictability to a more noteworthy broaden. Associated with the comparable line of advancement, this work likewise proposes time limited encryption and unscrambling calculations, which can separate between the comparable and unique areas and decrease the time intricacy further. The proposed algorithm demonstrates nearly 40% improvements over the standard encryption algorithms.
Keywords: Key Generation, Quartic Polynomial, Polynomial Randomization, Key Frame Similarity, Similarity Region Extractor, Adaptive Progression, Time Restricted Encryption, Time Restricted Decryption.
Scope of the Article: Next Generation Internet & Web Architectures