Fully Reversible Privacy Region Protection for Cloud Video Surveillance
Open accessAbstract
Privacy becomes one of the major concerns of cloud-based multimedia applications such as cloud video surveillance. Privacy protection of surveillance videos aims to protect privacy information without hampering normal processing tasks of the cloud. Privacy Region Protection only protects the privacy region while keeping the non-privacy region visually intact to facilitate processing in the cloud. However, full reversibility, i.e. the complete recovery of the original video which is critical to digital investigation and law enforcement has not been properly addressed in privacy region protection. In this paper, we introduce fully reversible privacy region protection into cloud video surveillance and propose a novel fully reversible privacy protection method for H.264/AVC compressed video. All the operations are performed in the compressed domain and avoid lossy re-encoding, so the original H.264/AVC compressed video can be fully recovered. To our best knowledge, the proposed scheme is the first fully reversible one for privacy region protection. Experimental results and performance comparison demonstrate the effectiveness and efficiency of the proposed approach.
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Traditional video streams are mainly transmitted and stored in a plaintext model, which leads to the risk of data leakage.
“Traditional video streams are mainly transmitted and stored in a plaintext model, which leads to the risk of data leakage [31,32].”
From Secure Video Surveillance Framework in Smart City (2021) · cites this paper as [32]
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A Systematic Review of Intelligence Video Surveillance: Trends, Techniques, Frameworks, and Datasets
Shidik, G. F., Noersasongko, E., Nugraha, A., Andono, P. N., Jumanto, J., & Kusuma, E. J. (2019) · IEEE Access · doi:10.1109/access.2019.2955387 · Cited by 114 · see citing works
Secure Video Surveillance Framework in Smart City
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- Authors
- Ma, X., Yang, L. T., Xiang, Y., Zeng, W. K., Zou, D., & Jin, H.
- Affiliations
- Huazhong University of Science and Technology (CN)
- St. Francis Xavier University (CA)
- Deakin University (AU)
- University of Missouri (US)
- Venue
- IEEE Transactions on Cloud Computing
- Published
- 2017-07-01
- Volume
- 5
- Issue
- 3
- Pages
- 510-522
- ISSN
- 2168-7161 (ISSN-L)
- OpenAlex
- W2526962699
- Cited by
- 25
- References
- 28
- Citations by year
- 2025: 1 · 2024: 2 · 2023: 1 · 2022: 2 · 2021: 1 · 2020: 9 · 2019: 7 · 2017: 1 · 2016: 1
- FWCI
- 0.81
- Type
- journal article
- Language
- en
- Open access
- green
- figshare.com
- Locations
- IEEE Transactions on Cloud Computing (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (61202302, 61272407, 61133008)
- National 973 Basic Research Program of China (2014CB340600)
- Program for New Century Excellent Talents in University (NCET-13-0241)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Video Coding and Compression Technologies
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Chaos-based Image/Signal Encryption
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Steganography and Watermarking Techniques
- Keywords
- H.264/AVC, compressed domain processing, video privacy, video recovery, digital investigation, law enforcement
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