Gray Hole Attack Detection and Prevention System in Vehicular Ad-Hoc Network (VANET)

EasyChair Preprint 6872

Abstract

VANET plays a key role in the development of smart transportation. In the transportation system traffic goes too fast and scales in number, which raises numerous challenges, especially in communication security. When vehicles transfer safety information with each other malicious attacks can destroy or alter the information. These attacks are of various types faced by VANET. So, there is a need to detect and prevent these attacks. In the Gray Hole attack, a network node receives RREQ packets and discovers a route to the destination. It drops few data packets after discovering a route [1]. Dropping against Gray Hole does not result in the loss of all data packets [2]. In this paper, the AODV routing protocol is used for the detection and prevention of Gray Hole attacks.

Objective:

• To generate a VANET scenario by introducing RSU and vehicle properties.
• To introduce Gray Hole attack on the network.
• To evaluate various parameters PDR, Packet loss, Collision avoidance, and throughput for performance evaluation.

Method and results: In the first phase of the proposed work VANET scenario has been designed by initializing Lanes, vehicles, and RSU. To eliminate this, information of neighboring nodes is collected and compared with the threshold values to find the malicious node [3]. The network simulator NS2 is used for the simulation process [4]. The number of nodes used by this network is 52 [5]. With help of the X graph performance of PDR, Throughput, Packet loss, delay are expressed  [6].

Conclusion: To identify malicious nodes available in the network for avoiding the collision neighbor node's information has been captured. We used PDR, PMOR & neighboring information. At last, we evaluate various parameters PDR, Packet loss, delay, and throughput for performance evaluation & based on these factors, we infer that our approach produces superior outcomes.

Keyphrases: AODV, Ad hoc, Gray hole attack, NS2, VANET, performance metrics

@booklet{EasyChair:6872,
  author    = {Gurtej Kaur and Meenu Khurana and Amandeep Kaur},
  title     = {Gray Hole Attack Detection and Prevention System in Vehicular Ad-Hoc Network (VANET)},
  howpublished = {EasyChair Preprint 6872},
  year      = {EasyChair, 2021}}