A comparative analysis of trust models for safety applications in IoT-enabled vehicular networks
Conference item
Ahmad, F., Adnane, Asma, Hussain, Rasheed and Kurugollu, Fatih 2019. A comparative analysis of trust models for safety applications in IoT-enabled vehicular networks. IEEE.
| Authors | Ahmad, F., Adnane, Asma, Hussain, Rasheed and Kurugollu, Fatih |
|---|---|
| Abstract | To achieve these goals, VANET requires a secure environment for authentic, reliable and trusted information dissemination among the network entities. However, VANET is prone to different attacks resulting in the dissemination of compromised/false information among network nodes. One way to manage a secure and trusted network is to introduce trust among the vehicular nodes. To this end, various Trust Models (TMs) are developed for VANET and can be broadly categorized into three classes, Entity-oriented Trust Models (ETM), Data oriented Trust Models (DTM) and Hybrid Trust Models (HTM). These TMs evaluate trust based on the received information (data), the vehicle (entity) or both through different mechanisms. In this paper, we present a comparative study of the three TMs. Furthermore, we evaluate these TMs against the different trust, security and quality-of-service related benchmarks. Simulation results revealed that all these TMs have deficiencies in terms of end-to-end delays, event detection probabilities and false positive rates. This study can be used as a guideline for researchers to design new efficient and effective TMs for VANET. |
| Keywords | Trust Models; Internet-of-Things; Smart Cities; Intelligent Transportation Systems; Vehicular Ad-hoc Network |
| Year | 2019 |
| Journal | IEEE Wireless Days |
| Publisher | IEEE |
| Web address (URL) | http://hdl.handle.net/10545/623715 |
| http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| hdl:10545/623715 | |
| File | File Access Level Open |
| File | File Access Level Open |
| File | |
| Publication dates | 13 Jun 2019 |
| Publication process dates | |
| Deposited | 26 Apr 2019, 13:14 |
| Accepted | 06 Feb 2019 |
| Rights | Attribution-NonCommercial-NoDerivs 3.0 United States |
| Contributors | University of Derby, Loughborough University and Innopolis University |
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