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Clone Detection Based on Physical Layer Reputation for Proximity Service
Univ Elect Sci & Technol China, Natl Key Lab Sci & Technol Commun, Chengdu 611731, Sichuan, Peoples R China..
ABB Corp Res, S-72226 Vasteras, Sweden..
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0002-5407-0835
Univ Elect Sci & Technol China, Dept Aeronaut & Astronaut, Chengdu 611731, Sichuan, Peoples R China..
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 3948-3957Article in journal (Refereed) Published
Abstract [en]

Proximity-based service (ProSe) provides direct communications among smart sensor nodes in proximity which aims at reserving resource consumption and alleviating the load in base stations, which is a promising solution for smart sensor systems that possess limited computing and energy resources. During the ProSe direct communications, most of the prior art security methods are usually provided by the ProSe function and are based on complex cryptography. However, despite the computing complexity, it is difficult for cryptographic methods to detect clone attack which is a common kind of attack in sensor systems. Clone nodes feature different physical positions but claim colliding IDs with captured nodes. Thus, clone nodes can be detected by spatial differences, in particular, by the surveillance of physical layer channel state information (CSI). However, CSI is not absolute static due to the random noise in wireless propagation environment. Accordingly, the detection accuracy varies with the stability of CSI. To address this challenge, we take the first attempt to introduce physical layer reputation and then elaborate the physical layer reputation based clone detection protocol to detect clone attack in multiple scenarios. The proposed protocol significantly improves the detection rate and false alarm rate and it is validated both by simulations and realizations.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 7, p. 3948-3957
Keywords [en]
Clone detection, proximity service, reputation based detection, smart sensor network
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-243966DOI: 10.1109/ACCESS.2018.2888693ISI: 000456189100001Scopus ID: 2-s2.0-85058903715OAI: oai:DiVA.org:kth-243966DiVA, id: diva2:1293017
Note

QC 20190301

Available from: 2019-03-01 Created: 2019-03-01 Last updated: 2019-03-01Bibliographically approved

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Xiao, Ming

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