Abstract
Video streaming service is popular in recent years and it provides numerous information to users all over the region. Since it needs to provide low latency and high quality-of-services (QoS) service to end users, the processing of video flows should be fast and can be finished real-time. As more and more people concern about their privacy in daily life, it is desirable to present privacy-preserving protocols in video streaming service. An authenticating and billing scheme is described in this paper to enable privacy-preserving sequential video streaming services. Two kinds of anonymous certificates are used. When connecting to the network, a pseudonym certificate as the proxy ticket is used to fetch proxy service for user’s node so as to request for proxy-based Internet access. Another pseudonym certificate as video subscribing ticket is shown when each user starts a pay-per-video session, and then only a hash value is needed for each sequential video. Pseudonym certificates can hide each user’s identity and easily-verifiable hash values enable quick sequential authentications. A temporary random key is selected to protect video streaming data so that the scheme can resist active man-in-middle attacks in many scenarios.
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Acknowledgment
This work is supported by National Natural Science Foundation of China, Grant (no. 61672411 and U1401251), National Key Research and Development Program of China Grant (no. 2017YFB0802201), Natural Science Basic Research Plan in Shaanxi Province of China, Grant (no. 2016JM6007), Major Basic Research Program of Shaanxi Province Natural Science Foundation Research Project (No. 2016ZDJC-04), China 111 Program (No. B16037) and the Research Fund for the Doctoral Program of Higher Education of China (No. 20130203120003). The authors gratefully acknowledge the anonymous reviewers for their valuable comments.
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Zhao, X., Li, H. (2017). Privacy Preserving Authenticating and Billing Scheme for Video Streaming Service. In: Wen, S., Wu, W., Castiglione, A. (eds) Cyberspace Safety and Security. CSS 2017. Lecture Notes in Computer Science(), vol 10581. Springer, Cham. https://doi.org/10.1007/978-3-319-69471-9_29
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DOI: https://doi.org/10.1007/978-3-319-69471-9_29
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