Aspects of Secure and Efficient Streaming and Collaboration

by Gunnar Kreitz

Doctoral Thesis, ISBN: 978-91-7415-942-4

Abstract

Research within the area of cryptography constitutes the core of this thesis. In addition to cryptography, we also present results in peer-assisted streaming and web security. We present results on two specific cryptographic problems: broadcast encryption and secure multi-party computation. Broadcast encryption is the problem of efficiently and securely distributing content to a large and changing group of receivers. Secure multi-party computation is the subject of how a number of parties can collaborate securely. All in all, this thesis spans from systems work discussing the Spotify streaming system with millions of users, to more theoretic, foundational results.

Streaming is among the largest applications of the Internet today. On-demand streaming services allow users to consume the media content they want, at their convenience. With the large catalogs offered by many services, users can access a wide selection of content. Live streaming provides the means for corporations as well as individuals to broadcast to the world. The power of such broadcasts was shown in the recent (early 2011) revolts in Tunisia and Egypt, where protesters streamed live from demonstrations.

To stream media to a large global audience requires significant resources, in particular in terms of the bandwidth needed. One approach to reduce the requirements is to use peer-to-peer techniques, where clients assist in distributing the media. Spotify is a commercial music-on-demand streaming system, using peer-to-peer streaming. In this thesis, we discuss the Spotify protocol and measurements on its performance.

In many streaming systems, it is important to restrict access to content. One approach is to use cryptographic solutions from the area of broadcast encryption. Within this area, we present two results. The first is a protocol which improves the efficiency of previous systems at the cost of lowered security guarantees. The second contains lower-bound proofs, showing that early protocols in the subset cover framework are essentially optimal.

Many streaming systems are web-based, where the user accesses content in a web browser. Apart from this usage of the web, subscriptions for streaming services are bought using a web browser. This means that to provide a secure streaming service, we must understand web security. This thesis contains a result on a new type of attack, using an old history detection vulnerability to time the execution of a redirect of a victim's browser.

Within the area of secure multi-party computation, this thesis has three contributions. Firstly, we give efficient protocols for the basic functions of summation and disjunction which adapt to the network they run on. Secondly, we provide efficient protocols for sorting and aggregation, by using techniques from the area of sorting networks. Finally, we prove a dichotomy theorem, showing that all functions with three distinct outputs are either maximally easy or maximally difficult with regards to the security provided.

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The thesis is comprised of an introduction, together with seven independent papers. You may be more interested in one of the individual papers instead of the thesis as a whole.

• Paper I: Spotify - Large Scale, Low Latency, P2P Music-on-Demand Streaming
• Paper II: A Zero-One Law for Secure Multi-Party Computation with Ternary Outputs
• Paper III: Secure Multi-Party Sorting and Applications
• Paper IV: Practical Private Information Aggregation in Large Networks
• Paper V: Timing is Everything - the Importance of History Detection
• Paper VI: Lower Bounds for Subset Cover Based Broadcast Encryption
• Paper VII: Stateful Subset Cover

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