Abstract
Due to the variety and rich features of live content, the live cloud platform has been widely used. However, they also bring the potential threat and huge vulnerability to the users’ privacy. At present, the security mechanism is simple in almost all live streaming cloud platforms. They generally use traditional security method such as Access Control List (ACL) to prevent unauthorized users from watching live streaming. In addition, they mainly consider the security of the system itself. These security measures can only guarantee the correct operation of the platform, and cannot guarantee that the privacy information of users in the platform is not leaked. Therefore, this paper proposes a privacy-preserving algorithm to protect private data of all participants in a live streaming cloud platform, including their follow relationships, live message, etc. According to semi-trusted live streaming cloud platforms, the proposed algorithm employs key exchange over elliptic curve and advanced encryption standard (AES) to preserve user privacy. A blind matching algorithm based on the encrypted tag is proposed to match the live message and intended recipients. Finally, the security of our algorithm is analyzed in depth and the results show the proposed algorithm efficiently preserves user privacy.
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Acknowledgments
This work was supported by the National Natural Science Foundation of China [grant numbers No. 61972352 and No. 61572435], the Natural Science Foundation of Zhejiang Province [grant number No. LZ16F020001 and No. LY17F020032].
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Xie, M., Sheng, X., Shao, J., Zhang, G., Ruan, Y. (2021). A User Privacy-Preserving Algorithm in Live Streaming Cloud Platforms. In: Wang, G., Chen, B., Li, W., Di Pietro, R., Yan, X., Han, H. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2020. Lecture Notes in Computer Science(), vol 12383. Springer, Cham. https://doi.org/10.1007/978-3-030-68884-4_19
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