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Department of Computer and Network Engineering

College of Information Technology


Using Similarity to Achieve Trust to Enhance Decision Making in Vehicular Safety Applications

Faculty Advisor

Dr. Hesham El-Sayed

Defense Date

24 November 2015


Vehicles exchange different types of messages either periodically or as needed for different types of

applications. The data in the network of vehicles can be used to extract valuable knowledge to support

various applications in vehicular ad hoc networks (VANETs). Knowledge gained from the gathered data

can be used to create local views of the network for individual vehicles; for instance, a vehicle can form a

view of a subset of the network using neighboring vehicles’ directions of travel, speeds, and the types of

applications they run. In the network, vehicles that have common attributes and requirements facilitate

the establishment of trust between them as these shared features make up the foundation for trust. Trust

relations between vehicles can be utilized for enhancing the performance and reliability of some applications.

This dissertation is concerned with trust establishment in VANETs, and how it can be utilized to enhance

efficiency and decision making in the network. We provide solutions to this question: How to utilize trust

relationship between vehicles to improve decision-making and efficiency in VANET safety applications.

In our research, we aim to establish trust relationships through similarity to assist vehicles in identifying

false safety messages in the network. We start by designing and implementing a trust management

system to generate and process trust values and to establish a set of trusted relationships for vehicles

running vehicular safety applications. Next, we explore the possibility of enhancing the decision-making

process using trust. First, we develop an analytical model that associates trust with the performance of

the decision-making process and the accuracy, and then we study the effectiveness of similarity-based

trust in identifying false safety event messages in VANETs. Finally, we show that similarity-based trust has

a positive impact on the time needed to make a decision and on the accuracy of that decision.


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