Bayesian fusion algorithm for inferring trust in wireless sensor networks

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dc.contributor.author Momani, M
dc.contributor.author Challa, S
dc.contributor.author Alhmouz, R
dc.date.accessioned 2012-02-02T10:56:21Z
dc.date.issued 2010-01
dc.identifier.citation Journal of Networks, 2010, 5 (7), pp. 815 - 822
dc.identifier.issn 1796-2056
dc.identifier.other C1 en_US
dc.identifier.uri http://hdl.handle.net/10453/15297
dc.description.abstract This paper introduces a new Bayesian fusion algorithm to combine more than one trust component (data trust and communication trust) to infer the overall trust between nodes. This research work proposes that one trust component is not enough when deciding on whether or not to trust a specific node in a wireless sensor network. This paper discusses and analyses the results from the communication trust component (binary) and the data trust component (continuous) and proves that either component by itself, can mislead the network and eventually cause a total breakdown of the network. As a result of this, new algorithms are needed to combine more than one trust component to infer the overall trust. The proposed algorithm is simple and generic as it allows trust components to be added and deleted easily. Simulation results demonstrate that a node is highly trustworthy provided that both trust components simultaneously confirm its trustworthiness and conversely, a node is highly untrustworthy if its untrustworthiness is asserted by both components.
dc.format Esha Dutt
dc.publisher Academy Publisher
dc.title Bayesian fusion algorithm for inferring trust in wireless sensor networks
dc.type Journal Article
dc.parent Journal of Networks
dc.journal.volume 7
dc.journal.volume 5
dc.journal.number 7 en_US
dc.publocation Finland en_US
dc.identifier.startpage 815 en_US
dc.identifier.endpage 822 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 0906 Electrical and Electronic Engineering
dc.personcode 040218
dc.personcode 104261
dc.percentage 100 en_US
dc.classification.name Electrical and Electronic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords Bayesian; Communication; Data; Fusion; Network; Sensor; Trust en_US
dc.description.keywords narrative research methods qualitative approaches nurse resilience
dc.description.keywords Bayesian
dc.description.keywords Communication
dc.description.keywords Data
dc.description.keywords Fusion
dc.description.keywords Network
dc.description.keywords Sensor
dc.description.keywords Trust
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Elec, Mech and Mechatronic Systems
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)


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