An Overview of Digital Video Watermarking

Asikuzzaman, Md.; Pickering, Mark

doi:10.1109/tcsvt.2017.2712162

Cited by 215 publications

(112 citation statements)

References 217 publications

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“…There has been extensive research into watermarking techniques [8] and some of the ideas developed in that field have applications in forgery prevention/detection, however, overall I consider it to be a tangential strain of research.…”

Section: Integrity Measuresmentioning

confidence: 99%

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Ahmed-Rengers

2019

Proceedings of the New Security Paradigms Workshop

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Video feeds are often deliberately used as evidence, as in the case of CCTV footage; but more often than not, the existence of footage of a supposed event is perceived as proof of fact in the eyes of the public at large. This reliance represents a societal vulnerability given the existence of easy-to-use editing tools and means to fabricate entire video feeds using machine learning. And, as the recent barrage of fake news and fake porn videos have shown, this isn't merely an academic concern, it is actively been exploited. I posit that this exploitation is only going to get more insidious. In this position paper, I introduce a long term project that aims to mitigate some of the most egregious forms of manipulation by embedding trustworthy components in the video transmission chain. Unlike earlier works, I am not aiming to do tamper detection or other forms of forensics -approaches I think are bound to fail in the face of the reality of necessary editing and compression -instead, the aim here is to provide a way for the video publisher to prove the integrity of the video feed as well as make explicit any edits they may have performed. To do this, I present a novel data structure, a video-edit specification language and supporting infrastructure that provides end-to-end video provenance, from the camera sensor to the viewer. I have implemented a prototype of this system and am in talks with journalists and video editors to discuss the best ways forward with introducing this idea to the mainstream.

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Section: Integrity Measuresmentioning

confidence: 99%

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Ahmed-Rengers

2019

Proceedings of the New Security Paradigms Workshop

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“…This method is used for the safe distribution of audio content over public networks, whereby only authorized users can access the high-quality content, while other users can only access a low-quality content [13]. Watermarks can be used in video files to identify pirates, which can be extracted at the decoder and used to determine whether the video content is watermarked [14]. We stress that our proposed scheme for integrating access control policies as watermarks can also be applied in audio files or video files, although we concentrate on images in this paper.…”

Section: Related Workmentioning

confidence: 99%

A Watermark-Based In-Situ Access Control Model for Image Big Data

Guo

Ren

et al. 2018

Future Internet

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When large images are used for big data analysis, they impose new challenges in protecting image privacy. For example, a geographic image may consist of several sensitive areas or layers. When it is uploaded into servers, the image will be accessed by diverse subjects. Traditional access control methods regulate access privileges to a single image, and their access control strategies are stored in servers, which imposes two shortcomings: (1) fine-grained access control is not guaranteed for areas/layers in a single image that need to maintain secret for different roles; and (2) access control policies that are stored in servers suffers from multiple attacks (e.g., transferring attacks). In this paper, we propose a novel watermark-based access control model in which access control policies are associated with objects being accessed (called an in-situ model). The proposed model integrates access control policies as watermarks within images, without relying on the availability of servers or connecting networks. The access control for images is still maintained even though images are redistributed again to further subjects. Therefore, access control policies can be delivered together with the big data of images. Moreover, we propose a hierarchical key-role-area model for fine-grained encryption, especially for large size images such as geographic maps. The extensive analysis justifies the security and performance of the proposed model

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“…It exploits the redundancy of digital images and embeds some information, namely watermark, into the images. According to different application situations, digital image watermarking scheme can be divided into three main categories [1]: Robust watermarking [2,3], fragile watermarking, and semi-fragile watermarking. The robust watermarking scheme can resist most attacks including signal processing attacks and some malicious attacks [4,5].…”

Section: Introductionmentioning

confidence: 99%

A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

2018

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Currently, the watermark capacity of most self-recovery fragile image watermarking schemes is fixed. That means for smooth regions and texture regions, the length of watermark information is always the same. However, it is impractical since more recovery information is needed for the recovery of texture regions. In this paper, a self-recovery fragile image watermarking with variable watermark capacity is proposed. Based on the characteristic of singular value decomposition (SVD), a new block classification method is introduced. The image blocks are classified into smooth blocks and texture blocks. For smooth blocks, the average pixel values are adopted as the recovery information to recover the tampered blocks, while for texture blocks, the quantized and coded DCT coefficients are adopted as the recovery information. After encrypted by binary pseudo-random sequence, the recovery watermark of each block is embedded into its mapping block. In the detection side, the three-level detection mechanism is applied to detect and locate the tampered regions. The experimental results prove that the proposed method achieves good tamper detection results, and the recovered image has better image quality than other self-recovery fragile watermarking methods.

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An Overview of Digital Video Watermarking

Cited by 215 publications

References 217 publications

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A Watermark-Based In-Situ Access Control Model for Image Big Data

A Self-Recovery Fragile Image Watermarking with Variable Watermark Capacity

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