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A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application

Author

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  • Chirag Sharma
  • Amandeep Bagga
  • Bhupesh Kumar Singh
  • Mohammad Shabaz

Abstract

The multimedia technologies are gaining a lot of popularity these days. Many unauthorized persons are gaining the access of multimedia such as videos, audios, and images. The transmission of multimedia across the Internet by unauthorized person has led to the problem of illegal distribution. The problem arises when copyrighted data is getting accessed without the knowledge of copyright owner. The videos are the most attacked data during COVID-19 pandemic. In this paper, the frame selection video watermarking technique is proposed to tackle the issue. The proposed work enlightens frame selection followed by watermarking embedding and testing of the technique against various attacks. The embedding of the watermark is done on selected frames of the video. The additional security feature Hyperchaotic Encryption is applied on watermark before embedding. Watermark embedding is done using graph-based transform and singular-valued decomposition and the performance of the technique is further optimized using hybrid combination of grey wolf optimization and genetic algorithm. Many researchers face the challenge of quality loss after embedding of watermark. Proposed technique will aim to overcome those challenges. A total of 6 videos (Akiyo, Coastguard, Foreman, News, Bowing, and Pure Storage) are used for carrying out research work. The performance evaluation of the proposed technique has been carried out after processing it against practical video processing attacks Gaussian noise, sharpening, rotation, blurring, and JPEG compression.

Suggested Citation

  • Chirag Sharma & Amandeep Bagga & Bhupesh Kumar Singh & Mohammad Shabaz, 2021. "A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-27, April.
  • Handle: RePEc:hin:jnlmpe:5580098
    DOI: 10.1155/2021/5580098
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    Cited by:

    1. Qiu Guo & Hechun Liu & Faez M. Hassan & Mohammed Wasim Bhatt & Ahmed Mateen Buttar, 2022. "Application of UAV tilt photogrammetry in 3D modeling of ancient buildings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 424-436, March.
    2. Wenzhong Xia & Rahul Neware & S. Deva Kumar & Dimitrios A. Karras & Ali Rizwan, 2022. "An optimization technique for intrusion detection of industrial control network vulnerabilities based on BP neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 576-582, March.
    3. Anshul Gupta & Pravin Srinath, 2022. "A recommender system based on collaborative filtering, graph theory using HMM based similarity measures," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 533-545, March.
    4. Gurpreet Singh Panesar & Kuldeep Narayan Tripathi & Jyoti L. Bangare & Rahul Neware & Skanda Moda Gururajarao, 2022. "Handling research issues for big data extraction in the application of Internet of Vehicles (IoV)," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 751-756, March.
    5. Guoyong Wang & Lokanayaki Karnan & Faez M. Hassan, 2022. "Face feature point detection based on nonlinear high-dimensional space," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 312-321, March.

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