StreamingTag: A Scalable Piracy Tracking Solution for Mobile Streaming Services

IF 7.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Transactions on Mobile Computing Pub Date : 2024-08-19 DOI:10.1109/TMC.2024.3445411
Fan Dang;Xinqi Jin;Qi-An Fu;Lingkun Li;Guanyan Peng;Xinlei Chen;Kebin Liu;Yunhao Liu
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Abstract

Streaming services have billions of mobile subscribers, yet video piracy has cost service providers billions. Digital Rights Management (DRM), however, is still far from satisfactory. Unlike DRM, which attempts to prohibit the creation of pirated copies, fingerprinting may be used to track out the source of piracy. Nevertheless, existing fingerprinting-based streaming systems are not widely used since they fail to serve numerous users. In this paper, we present the design and evaluation of StreamingTag, a scalable piracy tracing system for mobile streaming services. StreamingTag adopts a segment-level fingerprint embedding scheme to remove the need of re-embedding the fingerprint into the video for each new viewer. The key innovations of StreamingTag include a scalable and CDN-friendly delivery framework, an accurate and lightweight temporal synchronization scheme, a polarized and randomized SVD watermarking scheme, and a collusion-resistant fingerprinting scheme. Experiment results show the good QoS of StreamingTag in terms of preparation latency, bandwidth consumption, and video fidelity. Compared with existing methods, the proposed three schemes improve the re-identification accuracy by 4-49x, the watermark extraction accuracy by 2.25x at most and 1.5x on average, and the recall rate of catching colluders by 26%.
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StreamingTag:移动流媒体服务的可扩展盗版跟踪解决方案
流媒体服务拥有数十亿移动用户,但盗版视频却让服务提供商损失数十亿美元。然而,数字版权管理(DRM)还远远不能令人满意。DRM 试图禁止制作盗版,而指纹识别则不同,它可以用来追踪盗版的源头。然而,现有的基于指纹识别的流媒体系统并没有得到广泛应用,因为它们无法为众多用户提供服务。本文介绍了针对移动流媒体服务的可扩展盗版追踪系统 StreamingTag 的设计和评估。StreamingTag 采用分段级指纹嵌入方案,无需为每个新观众将指纹重新嵌入视频。StreamingTag 的主要创新包括:可扩展且对 CDN 友好的传输框架、精确且轻量级的时间同步方案、极化且随机的 SVD 水印方案以及抗串通的指纹方案。实验结果表明,StreamingTag 在准备延迟、带宽消耗和视频保真度方面具有良好的服务质量。与现有方法相比,所提出的三种方案的再识别准确率提高了 4-49 倍,水印提取准确率最多提高了 2.25 倍,平均提高了 1.5 倍,捕获串通者的召回率提高了 26%。
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来源期刊
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing 工程技术-电信学
CiteScore
12.90
自引率
2.50%
发文量
403
审稿时长
6.6 months
期刊介绍: IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.
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