RBATMWSN: Recursive Bayesian approach to trust management in wireless sensor networks

Momani, M; Aboura, K; Challa, S

RBATMWSN: Recursive Bayesian approach to trust management in wireless sensor networks

Momani, M Aboura, K Challa, S

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP, 2007, pp. 347 - 352
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Momani, M	en_US
dc.contributor.author	Aboura, K	en_US
dc.contributor.author	Challa, S	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP, 2007, pp. 347 - 352	en_US
dc.identifier.isbn	1424415020	en_US
dc.identifier.isbn	9781424415021	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2606
dc.description.abstract	This paper introduces a new trust model and a reputation system for wireless sensor networks based on a sensed continuous data. It establishes the continuous version of the beta reputation system introduced in [1] and applied to binary events and presents a new Gaussian Reputation System for Sensor Networks (GRSSN) . We introduce a theoretically sound Bayesian probabilistic approach for mixing second-hand information from neighbouring nodes with directly observed information. ©2007 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/LP0561200
dc.relation.ispartof	Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP	en_US
dc.relation.isbasedon	10.1109/ISSNIP.2007.4496868	en_US
dc.title	RBATMWSN: Recursive Bayesian approach to trust management in wireless sensor networks	en_US
dc.type	Conference Proceeding
utslib.for	0902 Automotive Engineering	en_US
dc.location.activity	Melbourne, Australia	en_US
pubs.embargo.period	Not known	en_US
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 Mechanical and Mechatronic Engineering
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

This paper introduces a new trust model and a reputation system for wireless sensor networks based on a sensed continuous data. It establishes the continuous version of the beta reputation system introduced in [1] and applied to binary events and presents a new Gaussian Reputation System for Sensor Networks (GRSSN) . We introduce a theoretically sound Bayesian probabilistic approach for mixing second-hand information from neighbouring nodes with directly observed information. ©2007 IEEE.

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http://hdl.handle.net/10453/2606