A Web Engineering-based Robust Watermark Restoration and Recognition Method for Protecting Online Video Content

Authors

  • Jieun Lee Dept. of Computer Science and Engineering, Soongsil University, Republic of Korea
  • Byeongchan Park Dept. of Computer Science and Engineering, Soongsil University, Republic of Korea
  • Uijin Jang Spartan SW Education Center, Soongsil University, Republic of Korea https://orcid.org/0000-0002-5082-509X
  • Yongtae Shin School of Computer Science and Engineering, Soongsil University, Republic of Korea

DOI:

https://doi.org/10.13052/jwe1540-9589.2441

Keywords:

Web video content, copyright protection, robustness indicators, digital watermark, feature point extracting and matching

Abstract

With the rapid expansion of over-the-top (OTT) services and web-based video streaming platforms, copyright protection has become a critical concern. Unauthorized redistribution and modification of digital content via composite transformations and distortions threaten content security. While watermarking and digital rights management (DRM) offer protection, existing methods often fail under real-world web-based attack scenarios. In this paper, we present a web engineering-based robust watermark restoration and recognition method to enhance the security of online video content. Our approach employs AKAZE feature detection to extract robust feature points, while a discrete wavelet transform (DWT) is used for subband decomposition, embedding the watermark in the lowest-energy subband near the detected feature points. To ensure resilience against distortions common in web environments, we evaluate our method under four types of noise (Gaussian, salt-and-pepper, uniform, and Poisson) and four rotation angles (0, 90, 180, and 270). AKAZE-based feature matching compensates for rotation distortions, while noise removal is handled using Gaussian, Median, or BM3D filtering. Performance evaluation using the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), normalized correlation (NC), and bit error rate (BER) confirms the effectiveness of our method. Results show that BM3D filtering achieves the highest average NC (0.8996) and the lowest BER (0.1137), demonstrating strong robustness against composite transformation attacks. This study contributes to web-based video security by integrating feature-based watermarking techniques with web engineering principles, ensuring effective protection for modern web applications.

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Author Biographies

Jieun Lee, Dept. of Computer Science and Engineering, Soongsil University, Republic of Korea

Jieun Lee received her B.Sc. in Aviation Information and Communication Engineering from Kyungwoon University, Republic of Korea, in 2023. Since 2023, she has been enrolled in the integrated M.Sc.-Ph.D. program in the Department of Computer Science and Engineering at Soongsil University, Republic of Korea. Her research interests include computer networks, artificial intelligence, cloud computing, and information security.

Byeongchan Park, Dept. of Computer Science and Engineering, Soongsil University, Republic of Korea

Byeongchan Park received his Bachelor’s degree in 2015 and his Master’s degree in computer engineering from Soongsil University in 2018, and his doctorate in computer engineering from Soongsil University in 2023. His research interests include copyright protection and utilization activation.

Uijin Jang, Spartan SW Education Center, Soongsil University, Republic of Korea

Uijin Jang received her Ph.D. in Computer Science and Engineering from Soongsil University, Republic of Korea, in 2010. Since 2018, she has been working at the Spartan SW Education Center at Soongsil University, Republic of Korea. Her research interests include networks, digital forensics, and DRM.

Yongtae Shin, School of Computer Science and Engineering, Soongsil University, Republic of Korea

Yongtae Shin received his Ph.D. in Computer Science from the University of Iowa in 1994. Since 1995, he has been serving as a Professor in the School of Computer Science and Engineering at Soongsil University, Republic of Korea. His research interests include computer networks, distributed computing, Internet protocols, and e-commerce technology.

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Published

2025-07-31

How to Cite

Lee, J. ., Park, B. ., Jang, U. ., & Shin, Y. . (2025). A Web Engineering-based Robust Watermark Restoration and Recognition Method for Protecting Online Video Content. Journal of Web Engineering, 24(04), 473–498. https://doi.org/10.13052/jwe1540-9589.2441

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Section

ECTI