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Practical Private Information Aggregation in Large Networks
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0001-5432-6442
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0003-4157-1371
2012 (English)In: Information Security Technology For Applications, Springer Berlin/Heidelberg, 2012, 89-103 p.Conference paper, Published paper (Refereed)
Abstract [en]

Emerging approaches to network monitoring involve large numbers of agents collaborating to produce performance or security related statistics on huge, partial mesh networks. The aggregation process often involves security or business-critical information which network providers are generally unwilling to share without strong privacy protection. We present efficient and scalable protocols for privately computing a large range of aggregation functions based on addition, disjunction, and max/min. For addition, we give a protocol that is information-theoretically secure against a passive adversary, and which requires only one additional round compared to non-private protocols for computing sums. For disjunctions, we present both a computationally secure, and an information-theoretically secure solution. The latter uses a general composition approach which executes the sum protocol together with a standard multi-party protocol for a complete subgraph of ``trusted servers''. This can be used, for instance, when a large network can be partitioned into a smaller number of provider domains.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2012. 89-103 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 7127
Keyword [en]
Multi-party computation, Private aggregation, Partial mesh
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-32420DOI: 10.1007/978-3-642-27937-9_7Scopus ID: 2-s2.0-84861636306ISBN: 978-364227936-2 (print)OAI: oai:DiVA.org:kth-32420DiVA: diva2:410598
Conference
15th Nordic Conference on Secure IT Systems, NordSec 2010;Espoo;27 October 2010 through 29 October 2010
Funder
ICT - The Next Generation
Note

QC 20110420

Available from: 2011-04-14 Created: 2011-04-14 Last updated: 2013-04-15Bibliographically approved
In thesis
1. Aspects of Secure and Efficient Streaming and Collaboration
Open this publication in new window or tab >>Aspects of Secure and Efficient Streaming and Collaboration
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Research within the area of cryptography constitutes the core of this the- sis. 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. Broad- cast 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 secu- rity 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.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2011. xi, 74 p.
Series
Trita-CSC-A, ISSN 1653-5723 ; 2011:05
National Category
Computer Science
Identifiers
urn:nbn:se:kth:diva-32424 (URN)978-91-7415-942-4 (ISBN)
Public defence
2011-05-13, D2, Lindstedtsvägen 5, KTH, Stockholm, 13:15 (English)
Opponent
Supervisors
Funder
ICT - The Next Generation
Note
QC 20110420Available from: 2011-04-20 Created: 2011-04-14 Last updated: 2012-06-14Bibliographically approved

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Citation style
  • apa
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