Identifying distinct features based on received samples for interference detection in wireless sensor network edge devices

dc.contributor.authorO'Mahony, George D.
dc.contributor.authorHarris, Philip J.
dc.contributor.authorMurphy, Colin C.
dc.contributor.funderIrish Research Councilen
dc.contributor.funderUnited Technologies Research Centeren
dc.date.accessioned2021-04-09T09:55:19Z
dc.date.available2021-04-09T09:55:19Z
dc.date.issued2020-04
dc.date.updated2021-04-09T09:43:26Z
dc.description.abstractWireless Sensor Network (WSN) technologies have developed considerably over the past decade or so and, now, feasible solutions exist for various applications, both critical and otherwise. Often these solutions are achieved by using commercial off the shelf components combined with standardized open-access protocols. As deployments diverge into safety-critical areas, attack incentives intensify, leading to persistent malicious intrusion challenges, which are ever-changing as interference techniques evolve and dynamic hardware becomes increasingly accessible. Unique WSN security vulnerabilities, a fluctuating radio frequency (RF) spectrum and physical environment and spectrum co-existence escalate the problem. Thus, securing WSNs is a critical and demanding requirement, heightened by the burden of protecting sensitive transmitted information. This paper, by utilizing ZigBee and Monte Carlo simulations, aims to develop an initial framework for interference detection in WSNs. Initially, bit error location analysis motivates a feature-based detection strategy, relating to both subtle and crude forms of interference. The work expands to analyze Matlab simulated error-free and erroneous transmissions to investigate whether feature useful differences exist. A feature set, including the measured probability density function of, and statistics on, the in-phase and quadrature-phase samples is demonstrated and initially validated/feasibility tested using a designed support vector machine.en
dc.description.sponsorshipIrish Research Council (IRC) and United Technologies Research Center Ireland (UTRC-I) (under the post-graduate Enterprise Partnership Scheme 2016, award number EPSPG/2016/66)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationO’Mahony, G. D., Harris, P. J. and Murphy, C. C. (2020) 'Identifying Distinct Features based on Received Samples for Interference Detection in Wireless Sensor Network Edge Devices', 2020 Wireless Telecommunications Symposium (WTS), Washington, DC, USA, 22-24 April, (7 pp). doi: 10.1109/WTS48268.2020.9198724en
dc.identifier.doi10.1109/WTS48268.2020.9198724en
dc.identifier.endpage7en
dc.identifier.isbn978-1-7281-4695-9
dc.identifier.isbn978-1-7281-4696-6
dc.identifier.issn1934-5070
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/11186
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers, IEEEen
dc.relation.urihttps://ieeexplore.ieee.org/document/9198724
dc.rights© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en
dc.subjectDetectionen
dc.subjectIEEE802.15.4en
dc.subjectInterferenceen
dc.subjectIoTen
dc.subjectMachine Learningen
dc.subjectSecurityen
dc.subjectSupport Vector Machineen
dc.subjectWSN and ZigBeeen
dc.titleIdentifying distinct features based on received samples for interference detection in wireless sensor network edge devicesen
dc.typeConference itemen
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