An Efficient Approach for the Detection and Prevention of Gray-Hole Attacks in VANETs

Vehicular Ad-Hoc Networks (VANETs) deliver a wide range of commercial as well safety applications and further motivate the advancements Internet Vehicles (IoV), Intelligent Transportation Systems (ITS), to Everything (V2X) communication. Despite their potential benefits, VANETs are susceptible variety security attacks due open, distributed, dynamic nature, which includes intrinsic protocol design issues. One such an infamous attack is Gray-Hole Attack (GHA), typically has two variants: Smart GHA Sequence Number-based GHA. In GHA, malicious node behaves normally during route discovery process, while in starts misbehaving process. either case, once successfully established, it dropping packets. this paper, novel approach called “Detection Prevention GHA” (DPGHA) proposed detect prevent both variants Ad Hoc On-Demand Distance Vector (AODV) based VANETs. The on generation threshold values abnormal differences received, forwarded, generated control or data packets among nodes sequence numbers. DPGHA implemented tested NS-2 SUMO simulators its various performances compared with most relevant benchmark approaches. results showed that performed better than approaches terms reduced routing overhead by 10.85% end-to-end delay 3.85%, increased Packet Delivery Ratio (PDR) 4.67% throughput 6.58%, achieved maximum detection rate 2.3%.