3.8 Proceedings Paper

A Formal Method of Trust Computation in VANET: A Spatial, Temporal and Behavioral Approach

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SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-031-20141-7_69

关键词

Formal method; Trust; Reputation; VANET

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VANET is a vehicle-assisted network that plays a key role in Intelligent Transportation Systems. It has safety and non-safety applications, but lacks a method to assess the behavior of certified vehicles. This study proposes a framework based on spatial, temporal, and behavioral parameters to compute the trust of vehicles.
VANETs (vehicular Ad-hoc Networks) are a subclass of Mobile Adhoc Networks (MANETs) that are currently playing a key role in Intelligent Transportation Systems (ITS). A VANET is a vehicle-assisted network that develops a dynamic topology over time. VANETs are developed to assist two sorts of applications: safety and non-safety. Non-safety applications ensure that vehicle occupants travel in safety and have access to essential entertainment, whereas safety applications are designed to protect people and public property. The existing VANET requirements are concerned with privacy and security issues, but they don't address how to assess the behavior of certified vehicles. A valid vehicle, for instance, could broadcast inaccurate data to a central monitoring system, causing the system to make an erroneous decision. Improved traffic safety and efficiency can be achieved via the use of VANET. However, in an untrusted environment, vehicles have difficulty determining the legitimacy of incoming messages. Trust, data accuracy, and dependability of data being broadcasted via the communication channel are the primary challenges in VANET. Depending on a variety of characteristics, vehicles can determine how trustworthy a given vehicle is based on how well it processes the received message. Therefore, a formal method of trust computation of vehicles is needed. The proposed framework is based on the spatial, temporal and behavioral paraments such as reputation, message correctness, participation degree, message similarity, message freshness, and vehicle age to compute the trust.

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