Hierarchical Hybrid Trust Management Scheme in SDN-Enabled VANETs

Abstract

One of the principal missions of security in the Internet of Vehicles (IoV) is to establish credible social relationships. The trust management system has been proved to be an effective security solution in a connected vehicle environment. The use of trust management can play a significant role in achieving reliable data collection and dissemination and enhanced user security in the Internet of Vehicles. However, due to a large number of vehicles, the limited computing power of individuals, and the highly dynamic nature of the network, a universal and flexible architecture is required to realize the trust of vehicles in a dynamic environment. The existing solutions for trust management cannot be directly applied to the Internet of Vehicles. To ensure the safe transmission of data between vehicles and overcome the problems of high communication delay and low recognition rate of malicious nodes in the current trust management scheme, an efficient flow forwarding mechanism of the RSU close to the controller in the Software-Defined Vehicular Network is used to establish a hierarchical hybrid trust management architecture. This method evaluates the dynamic trust change of vehicle behavior based on the trust between vehicles and the auxiliary trust management of the infrastructure to the vehicle, combined with static and dynamic information and other indicators. The proposed trust management scheme is superior to the comparative schemes in resisting simple attacks, selective misbehavior attacks, and time-dependent attacks under the condition of ensuring superior real-time performance. Its overall accuracy is higher than that of the baseline scheme.

Towards Strengthening the Resilience of IoV Networks—A Trust Management Perspective

“…Sarah [25] used the similarity, family and packet delivery ratio; in [26], the quality of received messages and the ability of nodes to disambiguate messages were used, as represented by Equation (1); and in [27], familiarity and package delivery rate were used to calculate direct trust, taking timeliness and interaction frequency as the weight of the trust calculation. Alnasser [28] calculated the trust value by using the forwarding rate of messages in time interval t, as shown in Equation ( 2); Ga [29] calculated direct trust by Bayesian inference and revised the trust value by penalty factor, as shown in Equation (3); Ji [30] used H t (j,k) to represent the legal behavior of node j to node k in a specific time period t; and Mao [31] used inter-vehicle subordinate trust weight and the original trust of the vehicle.…”

“…Ahmad [26] used positive opinions and negative opinions, as shown in Equation (4). Alnasser [28] first calculated the confidence value between two adjacent nodes; then, they divided all recommendations into positive recommendations and negative recommendations, and finally, they gave different weights to the two recommendations, as shown in Equation ( 5); Ga [29] used reputation to calculate the indirect trust value, as shown in Equation ( 6); Ji [30] used a cosine-based similarity metric and trust ratings and then used Resnick's standard prediction formula to calculate the recommended trust value; and Mao [31] used the role-based trust weight, the trust opinion of neighbors and the original trust of the vehicle;…”

“…Similarity-This parameter is used to measure the similarity in content and service between any two vehicles. Generally expressed as the Euclidean distance, the authors of [31] used the concept of similarity to calculate the similarity between the vehicle information in the infrastructure trust table and the information sent to the vehicle. • Familiarity-Familiarity indicates the familiarity between the trustor and the trustee, which is a parameter with a high utilization rate.…”

“…Whitewashing Attack/Newcomer Attack During a whitewashing attack, a node has a bad history before entering the system, but after re-entering the system, the node adopts a new identity in order to gain more trust and erase its dark history. In order to resist such attacks, in [31], new nodes were given a relatively low trust value, and an adaptive attenuation factor was also introduced so that the trust value of newcomers could reach a relatively high value over a long period of time.…”

On trust management in vehicular ad hoc networks: A comprehensive review

“…The separation of the control and data planes, as well as open programmability, are key features of SDN. According to current study, SDN can handle the time-varying nature of VANETs at a significantly reduced cost due to simplified hardware, software, and maintenance, as well as large-scale unified abstraction optimization (Xie et al, 2019;Mao et al, 2021). Mao et al (2021) established a hierarchical hybrid trust management architecture using an efficient flow forwarding mechanism of the RSU close to the controller in the Software-Defined Vehicular Network (SDVN), with the goal of overcoming the problems of high communication delay and low recognition rate of malicious nodes.…”