TACASHI: Trust-Aware Communication Architecture for Social Internet of Vehicles

The Internet of Vehicles (IoV) has emerged as a new spin-off research theme from traditional vehicular ad hoc networks. It employs vehicular nodes connected to other smart objects equipped with a powerful multisensor platform, communication technologies, and IP-based connectivity to the Internet, th...

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Veröffentlicht in:IEEE internet of things journal 2019-08, Vol.6 (4), p.5870-5877
Hauptverfasser: Kerrache, Chaker Abdelaziz, Lagraa, Nasreddine, Hussain, Rasheed, Ahmed, Syed Hassan, Benslimane, Abderrahim, Calafate, Carlos T., Cano, Juan-Carlos, Vegni, Anna Maria
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Sprache:eng
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Zusammenfassung:The Internet of Vehicles (IoV) has emerged as a new spin-off research theme from traditional vehicular ad hoc networks. It employs vehicular nodes connected to other smart objects equipped with a powerful multisensor platform, communication technologies, and IP-based connectivity to the Internet, thereby creating a possible social network called Social IoV (SIoV). Ensuring the required trustiness among communicating entities is an important task in such heterogeneous networks, especially for safety-related applications. Thus, in addition to securing intervehicle communication, the driver/passengers honesty factor must also be considered, since they could tamper the system in order to provoke unwanted situations. To bridge the gaps between these two paradigms, we envision to connect SIoV and online social networks (OSNs) for the purpose of estimating the drivers and passengers honesty based on their OSN profiles. Furthermore, we compare the current location of the vehicles with their estimated path based on their historical mobility profile. We combine SIoV, path-based and OSN-based trusts to compute the overall trust for different vehicles and their current users. As a result, we propose a trust-aware communication architecture for social IoV (TACASHI). TACASHI offers a trust-aware social in-vehicle and intervehicle communication architecture for SIoV considering also the drivers honesty factor based on OSN. Extensive simulation results evidence the efficiency of our proposal, ensuring high detection ratios >87% and high accuracy with reduced error ratios, clearly outperforming previous proposals, known as RTM and AD-IoV.
ISSN:2327-4662
2327-4662
DOI:10.1109/JIOT.2018.2880332