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R2SCDT: robust and reliable secure clustering and data transmission in vehicular ad hoc network using weight evaluation - 2021

R2SCDT: robust and reliable secure clustering and data transmission in vehicular ad hoc network using weight evaluation

Research Area:  Vehicular Ad Hoc Networks


Vehicular ad hoc networks (VANETs) gained the probable to change transportations perspectives using wireless communication network entities such as buses, cars, cell phones, traffic signals, etc. But factors like the heavy reliance on control technologies, computing, communication, severe mobility, etc. lead to several vulnerabilities in the network. The communication among two vehicles in VANETs should be secure as it mainly includes one or more intermediate vehicles to forward the data from the source to the objective. Hence the intermediate vehicles must be reliable for guaranteed data transmission. The malicious nodes may become part of such communications that can accept the data and drop (or misuse) data to create congestion. This paper proposed the Robust and Reliable Secure Clustering and Data Transmission (R2SCDT/RRSCDT) protocol to mitigate the challenges of malicious vehicles in the network. The methodology is dependent on the trust evaluation of vehicles to detect malicious nodes for secure Cluster Head (CH) selection and data transmission. The clustering performs to isolate the vehicles into clusters and choose the CH for each cluster. The CH choice performed using the trust evaluation of each vehicle and detects the attackers with less trust value. During the data transmission phase, the nodes are selected via the trust evaluation model and raise the alarm if any node has been detected as malicious. The purpose of trust-based clustering and data transmission functionality R2SCDT is to achieve guaranteed QoS performance with minimum time and control overheads. The simulation result shows the proposed model significantly improves performance compared to state-of-art security solutions of VANET.


Author(s) Name:  Sridevi Hosmani & Basavaraj Mathapati

Journal name:  Journal of Ambient Intelligence and Humanized Computing

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s12652-021-03414-3

Volume Information: