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Feature-Based Multi-User Authentication for Parallel Uplink Transmissions
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9307-484X
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-6682-6559
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-7926-5081
2016 (English)In: 2016 9TH INTERNATIONAL SYMPOSIUM ON TURBO CODES AND ITERATIVE INFORMATION PROCESSING (ISTC), IEEE, 2016, 355-359 p.Conference paper (Refereed)
Abstract [en]

We study a multi-user up-link scenario where an attacker tries to impersonate the legitimate transmitters. We present a new framework for deriving a posteriori attack probabilities from the channel observations at the access point, which enables fast intrusion detection and authentication at the physical layer and can be exploited to reduce the security overhead by offtoading higher-layer authentication schemes. This is highly relevant for delay-sensitive applications that are targeted in 5G where the security overhead may limit the real-time performance. We take a factor-graph approach that can easily be extended to take into account other features, channel models, and radio access schemes. While related works only consider single-link scenarios, the multi-user approach in this paper allows us to exploit the cross-channel correlation of the large-scale fading parameters that is due to the propagation environment for improving the detection performance. As numerical results show, especially for slowly changing channels with high correlation our approach provides significant performance gains.

Place, publisher, year, edition, pages
IEEE, 2016. 355-359 p.
Series
International Symposium on Turbo Codes and Iterative Information Processing, ISSN 2165-4700
National Category
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-197023DOI: 10.1109/ISTC.2016.7593136ISI: 000386655300072ScopusID: 2-s2.0-84994415945ISBN: 978-1-5090-3401-7 (print)OAI: oai:DiVA.org:kth-197023DiVA: diva2:1054792
Conference
9th International Symposium on Turbo Codes and Iterative Information Processing (ISTC), SEP 05-09, 2016, Brest, FRANCE
Note

QC 20161209

Available from: 2016-12-09 Created: 2016-11-28 Last updated: 2016-12-09Bibliographically approved

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Forssell, HenrikThobaben, RagnarGross, JamesSkoglund, Mikael
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