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dc.contributor.authorIngham, Maxen_UK
dc.contributor.authorMarchang, Jimsen_UK
dc.contributor.authorBhowmik, Deepayanen_UK
dc.description.abstractInternet of Things (IoT) gains popularity in recent times due to its flexibility, usability, diverse applicability and ease of deployment. However, the issues related to security is less explored. The IoT devices are light weight in nature and have low computation power, low battery life and low memory. As incorporating security features are resource expensive, IoT devices are often found to be less protected and in recent times, more IoT devices have been routinely attacked due to high profile security flaws. This paper aims to explore the security vulnerabilities of IoT devices particularly that use Low Power Wide Area Networks (LPWANs). In this work, LoRaWAN based IoT security vulnerabilities are scrutinised and loopholes are identified. An attack was designed and simulated with the use of a predictive model of the device data generation. The paper demonstrated that by predicting the data generation model, jamming attack can be carried out to block devices from sending data successfully. This research will aid in the continual development of any necessary countermeasures and mitigations for LoRaWAN and LPWAN functionality of IoT networks in general.en_UK
dc.publisherInstitution of Engineering and Technologyen_UK
dc.relationIngham M, Marchang J & Bhowmik D (2020) IoT Security Vulnerabilities and Predictive Signal Jamming Attack Analysis in LoRaWAN. IET Information Security, 14 (4), pp. 368-379.
dc.rightsThis paper is a postprint of a paper submitted to and accepted for publication in IET Information Security and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Library.en_UK
dc.subjectwide area networksen_UK
dc.subjectInternet of Thingsen_UK
dc.subjectcomputer network securityen_UK
dc.titleIoT Security Vulnerabilities and Predictive Signal Jamming Attack Analysis in LoRaWANen_UK
dc.typeJournal Articleen_UK
dc.citation.jtitleIET Information Securityen_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.affiliationSheffield Hallam Universityen_UK
dc.contributor.affiliationSheffield Hallam Universityen_UK
dc.contributor.affiliationComputing Scienceen_UK
Appears in Collections:Computing Science and Mathematics Journal Articles

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