| Title | A Feedback-Driven Lightweight Reputation Scheme for IoV |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Dahiya, Rohan, Jiang, Frank, Doss, Robin Ram |
| Conference Name | 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) |
| Date Published | dec |
| Keywords | Bogus Information Attack., false trust, Information filters, Internet, Internet of Vehicles(IoV), policy-based governance, privacy, pubcrawl, reputation system, Resiliency, Scalability, security, statistical analysis, Trust management, V2X, VANET, Vehicle dynamics |
| 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. |
| DOI | 10.1109/TrustCom50675.2020.00141 |
| Citation Key | dahiya_feedback-driven_2020 |
A Feedback-Driven Lightweight Reputation Scheme for IoV