P3LS: Plausible Deniability for Practical Privacy-Preserving Live Streaming

Abstract

Video consumption is one of the most popular Internet activities worldwide. The emergence of sharing videos directly recorded with smartphones raises important privacy concerns. In this paper we propose P3LS, the first practical privacy-preserving peer-to-peer live streaming system. To protect the privacy of its users, P3LS relies on k-anonymity when users subscribe to streams, and on plausible deniability for the dissemination of video streams. Specifically, plausible deniability during the dissemination phase ensures that an adversary is never able to distinguish a user's stream of interest from the fake streams from a statistical analysis (i.e., using an analysis of variance). We exhaustively evaluate P3LS and show that adversaries are not able to identify the real stream of a user with very high confidence. Moreover, P3LS consumes 30% less bandwidth than the standard k-anonymity approach where nodes fully contribute to the dissemination of k streams.

A Contemporary Survey on Live Video Streaming from a Computation-Driven Perspective

“…The results in [141] have shown the security and privacy outperformance of their proposal compared with a system without HIPE. In [38], the practical privacy-preserving live streaming, called P3LS, was irst proposed to protect the privacy of multiple streams in P2P LVS, where the evaluation of P3LS not only showed the privacy contribution but also 30% less bandwidth consumption than the non-P3LS strategy. Because the energy issue has become crucial in the mobile platform, Samet et al [146] investigated the energy consumption comparison among the triple data encryption standard (3DES), advanced encryption standard (AES), and Blowish algorithms for video streaming services.…”

“…Proposed the HIPE algorithm and broker with an anonymous pubsub architecture to provide security and privacy outperformance [38] Proposed P3LS algorithm to protect the privacy of multiple streams in P2P LVS [146] Investigated the energy consumption comparison among 3DES, AES, and Blowish [168] Utilized the face recognition of privacy-aware architecture to further enhance security is increasingly dominant in 5G ecosystems and beyond, LVS frameworks should provide scalability to adaptively serve a massive number of user requests with various streaming lows simultaneously. Because user interests are spatiotemporal patterns, LVS capabilities must be lexibly elastic to any luctuations of service request volumes and distributions in both the time and space domains.…”

PrivaTube

“…Decouchant et al [21] developed concurrently to our work a technique similar to our use of fake requests, but for pure peer-to-peer video streaming, i.e. without any video servers.…”