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A Counter-Eavesdropping Technique for Optimized Privacy of Wireless Industrial IoT Communications
journal contribution
posted on 2022-09-29, 01:57 authored by J H Anajemba, C Iwendi, Imran RazzakImran Razzak, J A Ansere, I M OkpalaoguchiThe industrial Internet of Things (IIoTs) is a key component of the fourth industrial revolution (Industry 4.0) which is faced with privacy issues as the scale and sensitivity of user and system data constantly increases. Eavesdropping attack is one of such privacy issue of the IIoT system especially when the number of transmitting antennas is increased. Thus, the focus of this article is on establishing efficient privacy in an IIoT-multiple-input-multiple-output-multiple-antenna eavesdropping communications scenario. To achieve this, a closed-form derivation for asymptotic regularized prompt privacy rate is first formulated for IIoT network system. Then, the study further examines the design of optimal jamming parameters by proposing a model referred as optimal counter-eavesdropping channel approximation technique for tackling eavesdropping attack in IIoT. The simulated performance of the proposed model clearly shows that provided that the channel coherence time is less than two times the number of transmitting nodes, a high privacy precision is achieved even without deploying any artificial noise.
History
Journal
IEEE Transactions on Industrial InformaticsVolume
18Issue
9Pagination
6445 - 6454Publisher DOI
ISSN
1551-3203eISSN
1941-0050Publication classification
C1.1 Refereed article in a scholarly journalUsage metrics
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No categories selectedKeywords
Science & TechnologyTechnologyAutomation & Control SystemsComputer Science, Interdisciplinary ApplicationsEngineering, IndustrialComputer ScienceEngineeringIndustrial Internet of ThingsData privacyFourth Industrial RevolutionData communicationTransmitting antennasEavesdroppingAuthenticationArtificial noisechannel state information (CSI)industrial Internet of Things (IIoTs)Industry 4multiple-input-multiple-output-multiple-antenna eavesdropping (MIMOME)privacy capacityINTERNETSECURITY
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