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Red-AODV: A Prevention Model of Black Hole Attack for VANET Protocols and Identification of Malicious Nodes in VANET


Affiliations
1 Department of Information and Communication Technology, Comilla University, Bangladesh
 

VANET is a type of MANET in which the Vehicle nodes communicate between each other using wireless medium without any fixed infrastructure. The major goal of VANET is to create a safer and more efficient Intelligent Transportation System (ITS) and Traffic Information System (TIS) where high-mobility drivers may communicate with one another. Routing protocols, we know, accomplish the shortest possible connection time while using the least amount of network resources. VANETs also have some routing protocols to implement it in the real world for proper communication among vehicles. The Black Hole Attack has become one of the security dangers in VANET because of the great mobility of the vehicles and the volatile nature of the network connections. As the name imply, the Black Hole Attack in VANET is similar to the Black Hole in the universe which makes entities disappeared. Black Hole Attack redirects the data packets to such a node that actually does not exist in the network. In this research, we analyzed the performances of one reactive protocol (AODV) and one proactive protocol (OLSR) in order to better categorize the protocol’s robustness under Black Hole Attack and approach a prevention model, named Red-AODV to keep VANET safe from Black Hole Attack. After applying the Red-AODV protocol in the network which may reduce the losses resulted from the existence of Black Hole Attack, then again we analyze the changings of the network performance. We use Network Simulator 2 and run it for different number of nodes. The simulations are made in terms of several network parameters including Packet Delivery Ratio (PDR), Dropped Packet Ratio (DPR) and End to End Delay (EED), Throughput and Normalized Routing Load (NRL).

Keywords

VANET, Black Hole Attack, AODV, Red-AODV, Intelligent Transport System.
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  • Red-AODV: A Prevention Model of Black Hole Attack for VANET Protocols and Identification of Malicious Nodes in VANET

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Authors

Md. Tofael Ahmed
Department of Information and Communication Technology, Comilla University, Bangladesh
Amina Aktar Rubi
Department of Information and Communication Technology, Comilla University, Bangladesh
Md. Saifur Rahman
Department of Information and Communication Technology, Comilla University, Bangladesh
Maqsudur Rahman
Department of Information and Communication Technology, Comilla University, Bangladesh

Abstract


VANET is a type of MANET in which the Vehicle nodes communicate between each other using wireless medium without any fixed infrastructure. The major goal of VANET is to create a safer and more efficient Intelligent Transportation System (ITS) and Traffic Information System (TIS) where high-mobility drivers may communicate with one another. Routing protocols, we know, accomplish the shortest possible connection time while using the least amount of network resources. VANETs also have some routing protocols to implement it in the real world for proper communication among vehicles. The Black Hole Attack has become one of the security dangers in VANET because of the great mobility of the vehicles and the volatile nature of the network connections. As the name imply, the Black Hole Attack in VANET is similar to the Black Hole in the universe which makes entities disappeared. Black Hole Attack redirects the data packets to such a node that actually does not exist in the network. In this research, we analyzed the performances of one reactive protocol (AODV) and one proactive protocol (OLSR) in order to better categorize the protocol’s robustness under Black Hole Attack and approach a prevention model, named Red-AODV to keep VANET safe from Black Hole Attack. After applying the Red-AODV protocol in the network which may reduce the losses resulted from the existence of Black Hole Attack, then again we analyze the changings of the network performance. We use Network Simulator 2 and run it for different number of nodes. The simulations are made in terms of several network parameters including Packet Delivery Ratio (PDR), Dropped Packet Ratio (DPR) and End to End Delay (EED), Throughput and Normalized Routing Load (NRL).

Keywords


VANET, Black Hole Attack, AODV, Red-AODV, Intelligent Transport System.

References





DOI: https://doi.org/10.22247/ijcna%2F2021%2F209985