Cloud-Based Multimedia Content Protection System

Authors

  • B. Aparna  Department of CSE, BITS Vizag, Visakhapatnam, Andhra Pradesh, India
  • S. Madhavi  Department of CSE, BITS Vizag, Visakhapatnam, Andhra Pradesh, India
  • G. Mounika  Department of CSE, BITS Vizag, Visakhapatnam, Andhra Pradesh, India
  • P. Avinash  Department of CSE, BITS Vizag, Visakhapatnam, Andhra Pradesh, India
  • S. Chakravarthi  Department of CSE, BITS Vizag, Visakhapatnam, Andhra Pradesh, India

DOI:

https://doi.org//10.32628/IJSRSET207448

Keywords:

Multi-cloud,distributed matching engine, depth signatures,k-nearest, auxiliary function, steoricscopic cotent, robust signatures.

Abstract

We propose a new design for large-scale multimedia content protection systems. Our design leverages cloud infrastructures to provide cost efficiency, rapid deployment, scalability, and elasticity to accommodate varying workloads. The proposed system can be used to protect different multimedia content types, including videos, images, audio clips, songs, and music clips. The system can be deployed on private and/or public clouds. Our system has two novel components: (i) method to create signatures of videos, and (ii) distributed matching engine for multimedia objects. The signature method creates robust and representative signatures of videos that capture the depth signals in these videos and it is computationally efficient to compute and compare as well as it requires small storage. The distributed matching engine achieves high scalability and it is designed to support different multimedia objects. We implemented the proposed system and deployed it on two clouds: Amazon cloud and our private cloud. Our experiments with more than 11,000 videos and 1 million images show the high accuracy and scalability of the proposed system. In addition, we compared our system to the protection system used by YouTube and our results show that the YouTube protection system fails to detect most copies of videos, while our system detects more than 98% of them.

References

  1. Mohamed Hefeeda, Tarek El Gamal, Kiana Calagari and Ahmed Abdelsadek,2015 IEEE,” Cloud based Multimedia Content Protection System”.
  2. R. Amirtharathna1, Mrs. P. Vijayasarathy,” Copy Detection of Multimedia Contents in Cloud”,2016, International Journal of Engineering and Computer Science.
  3. Vaishali Dewar, Priya Pise,” A Mechanism for Copyrighted Video Copy Detection and Identification”,2015, International Journal of Science and Research (IJSR).
  4. A. Perumal Raja, B. Venkadesan,” Efficient Framework for Video Copy Detection Using Segmentation and Graph-Based Video Sequence Matching”,2014., IEEE Paper.
  5. Pratheep Anantharatnasamy, Kaavya Sriskandaraja, Vahissan Nandakumar,” Fusion of Colour, Shape and
  6. Texture Features for content-based image retrival”,2013, International Journal of Science and Research (IJSR).
  7. M. Ramya, R. Kanthvel,” Efficient and Scalable Content- based Video Copy Detection System”,2012, International Journal of Computer Applications® (IJCA).
  8. Vishwa Gupta, Parisa Darvish Zadeh Varcheie,2012,” Content-based video copy detection using nearest neighbor mapping.

International Journal of Scientific Research in Science, Engineering and Technology

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Published

2020-08-30

Issue

Volume 7, Issue 4, July-August-2020

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
B. Aparna, S. Madhavi, G. Mounika, P. Avinash, S. Chakravarthi, " Cloud-Based Multimedia Content Protection System, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 7, Issue 4, pp.164-169, July-August-2020. Available at doi : https://doi.org/10.32628/IJSRSET207448