A Feedback-Driven Lightweight Reputation Scheme for IoV

Dahiya, R; Jiang, F; Doss, RR

A Feedback-Driven Lightweight Reputation Scheme for IoV

Dahiya, R Jiang, F

Doss, RR

Permalink

Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2021, 00, pp. 1060-1068
Issue Date:: 2021-02-09

Closed Access

	Filename	Description	Size
	A_Feedback-Driven_Lightweight_Reputation_Scheme_for_IoV.pdf	Published version	536.75 kB		View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Dahiya, R
dc.contributor.author	Jiang, F https://orcid.org/0000-0003-3765-561X
dc.contributor.author	Doss, RR
dc.date	2020-12-29
dc.date.accessioned	2022-01-04T00:29:44Z
dc.date.available	2022-01-04T00:29:44Z
dc.date.issued	2021-02-09
dc.identifier.citation	2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2021, 00, pp. 1060-1068
dc.identifier.isbn	978-1-6654-0392-4
dc.identifier.issn	2324-898X
dc.identifier.issn	2324-9013
dc.identifier.uri	http://hdl.handle.net/10453/152623
dc.description.abstract	Most applications of Internet of Vehicles (IoVs) rely on collaboration between nodes. Therefore, false information flow in-between these nodes poses the challenging trust issue in rapidly moving IoV nodes. To resolve this issue, a number of mechanisms have been proposed in the literature for the detection of false information and establishment of trust in IoVs, most of which employ reputation scores as one of the important factors. However, it is critical to have a robust and consistent scheme that is suitable to aggregate a reputation score for each node based on the accuracy of the shared information. Such a mechanism has therefore been proposed in this paper. The proposed system utilises the results of any false message detection method to generate and share feedback in the network, this feedback is then collected and filtered to remove potentially malicious feedback in order to produce a dynamic reputation score for each node. The reputation system has been experimentally validated and proved to have high accuracy in the detection of malicious nodes sending false information and is robust or negligibly affected in the presence of spurious feedback.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
dc.relation.ispartof	2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications
dc.relation.isbasedon	10.1109/trustcom50675.2020.00141
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	A Feedback-Driven Lightweight Reputation Scheme for IoV
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Guangzhou, China
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Provost
pubs.organisational-group	/University of Technology Sydney/Provost/Jumbunna
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-01-04T00:29:43Z
pubs.finish-date	2021-01-01
pubs.place-of-publication	Piscataway, USA
pubs.publication-status	Published
pubs.start-date	2020-12-29
pubs.volume	00
dc.location	Piscataway, USA

Abstract:

Most applications of Internet of Vehicles (IoVs) rely on collaboration between nodes. Therefore, false information flow in-between these nodes poses the challenging trust issue in rapidly moving IoV nodes. To resolve this issue, a number of mechanisms have been proposed in the literature for the detection of false information and establishment of trust in IoVs, most of which employ reputation scores as one of the important factors. However, it is critical to have a robust and consistent scheme that is suitable to aggregate a reputation score for each node based on the accuracy of the shared information. Such a mechanism has therefore been proposed in this paper. The proposed system utilises the results of any false message detection method to generate and share feedback in the network, this feedback is then collected and filtered to remove potentially malicious feedback in order to produce a dynamic reputation score for each node. The reputation system has been experimentally validated and proved to have high accuracy in the detection of malicious nodes sending false information and is robust or negligibly affected in the presence of spurious feedback.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/152623