Intrusion prevention system for DDoS attack on VANET with reCAPTCHA controller using information based metrics

Abstract

Due to the dynamic in nature, the vulnerabilities that exist in VANET are much higher when compared with that of the wired network infrastructure. In DoS attacks, the legitimate users are prohibited from accessing the services or network resource. The primary goal of the attack to make the desired destination vehicle unavailable or relegate the message all the way through the network affects the reachability. The proposed reCAPTCHA controller mechanism prevents the automated attacks similarly like botnet zombies. The reCAPTCHA controller is used to check and prohibit most of the automated DDoS attacks. For implementing this technique, the information theory based metric is used to analyze the deviation in users request in terms of entropy. Frequency and entropy are the metrics used to measure the vulnerability of the attack. The stochastic model based reCAPTCHA controller is used as a prevention mechanism for the large botnet based attackers. To inspect the efficiency of the proposed method, various network parameters are considered such as Packet Delivery Ratio (PDR), Average Latency (AL), Detection Rate (DR) and Energy Consumption (EC). In the proposed research work, the metric PDR is used to know successful delivery of data packets to the destination vehicle without any interrruption. These parameters are used to measure how effectively the data is delivered to the destination from source vehicle.