PDBTM-IOV: Probability Distribution Based Trust Model for Internet of Vehicles

In Internet of vehicle network, security of data transmitted by nodes is of Prime concern. This paper presents an algorithm for effectively classifying the trustworthy and non-trust worthy nodes for secure communication of vehicles. The categorization is done based on probability distribution curve drawn using statistics of nodes. The nodes will be considered as normal when the PDF of the nodes lies in the range of mean +/-2 standard deviation of the curve. Simulation is performed for three trust threshold $(\theta=0.65,0.7,0.75)$ and two metrics i.e. trust value and Packet delivery ratio. The proposed model is compared with rater and ratee based model in terms of transaction number growth. From the results, it can be found that average trust maximizes with time for trusted nodes and becomes zero non trusted nodes. Results also depicts that the Packet Delivery Ratio is 0.065 for normal nodes and 0.015 for abnormal nodes. The proposed model distinguishes between trusted and malicious nodes efficiently, providing a better, scalable and lightweight trust mechanism for IoV environments without relying on cryptographic methods. Future work will focus on improving the model's adaptability to real-world network conditions and incorporating dynamic trust thresholds for greater accuracy in various vehicular scenarios.