Work place: Department of Electrical and Computer Engineering, Michigan Technological University, Houghton, MI-49931, USA
E-mail: mtabassu@mtu.edu
Website:
Research Interests: Signal Processing, Wireless Communication, Wireless Networks, Computer Networks
Biography
Mehnaz Tabassum received her B.Sc. degree in Applied Physics, Electronics and Communication Engineering, and the M.Sc. degree in Electrical and Electronic Engineering from University of Dhaka, Bangladesh, in 2014 and 2016, respectively. She is currently pursuing her Ph.D. degree in Electrical and Computer Engineering from Michigan Technological University, Houghton, MI, USA. Her research interest is Vehicular Communication, Vehicular Networking, Signal Processing and Wireless Communication.
By Mehnaz Tabassum Aurenice Oliveira
DOI: https://doi.org/10.5815/ijwmt.2022.04.01, Pub. Date: 8 Aug. 2022
The ever need for transportation safety, faster and convenient travel, decrease in energy consumption, as well as inter-connectivity has led to the field of intelligent transportation system (ITS). At the core of ITS is the Internet of Vehicles (IoV) combining hardware/sensors, software, and network technologies. Vehicular ad hoc networks (VANETs) create mechanisms to connect IoV main elements, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and Vehicle-to-Sensors (V2S). ITS systems heavily rely on its network connecting different parts of its infrastructure and ensuring data exchanges. However, VANET security is one of the primary challenges faced by connected vehicles. In IoV, the network is accessed by a variety device making the system vulnerable to a multitude of malicious attacks, including distributed denial-of-service (DDoS) and black hole attacks. Since critical vehicle systems can be accessed remotely, successful attacks can lead to fatalities. In VANET, any node can function as a router for the other nodes, therefore a malicious node connected to the network may inject spoofed routing tables to the other nodes thereby affecting the operation of the entire network. To overcome this issue, we proposed a security scheme designed to improve routing protocols in the detection of black hole attack. The proposed approach is demonstrated on a Network Simulator (NS3.27) using different network parameters such as average packet loss rate, end-to-end delay, packet delivery ratio (PDR) and network yield. Simulation results demonstrate the proposed method adds 10-15% improvement (on average) in End-to-End Delay, Packet Delivery Rate, Packet Loss Rate and Network Yield as compared with conventional Greedy Parameter Stateless Routing and Path Aware Greedy Parameter Stateless Routing under the black hole attack.
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