Modeling and Detection of Flooding-Based Denial of Service Attacks in Wireless Ad Hoc Networks Using Uncertain Reasoning

Wireless Ad Hoc Networks are self-organizing networks deployed without any centralized infrastructure. Flooding based Denial-of-Service (DoS) attacks were targeting the constrained resources of mobile nodes as well as the network. Route Request (RREQ) flooding attack is one of the prominent DoS attacks launched from the network layer in which the attacker sends a huge number of spoofed Route Request (RREQ) packets which not only overflows the target buffer but also creates network congestion. In this work, novel methods were suggested for defending RREQ flooding attack in Wireless Ad Hoc Network using two well-known frameworks in uncertain reasoning namely Bayesian Inference and Dempster-Shafer (D-S) evidence theory. The present work reports the modeling of RREQ traffic and developed an optimum algorithm for the detection of persistent RREQ flooding attack using Bayesian Inference. The algorithm was further refined for the detection of high rate and low rate pulsed RREQ flooding attack using D-S evidence theory. Based on the comprehensive evaluation using mathematical modeling and simulation, the proposed method successfully defended any type of flooding based DoS attack in Wireless Ad Hoc Network with lower communication and memory overhead.

Automated summary

This study proposes novel methods for defending against RREQ flooding attacks in Wireless Ad Hoc Networks using Bayesian Inference and Dempster-Shafer (D-S) evidence theory. The algorithms can detect persistent attacks as well as high rate and low rate pulsed attacks. Through mathematical modeling and simulation evaluations, the proposed method successfully defends against any type of flooding based DoS attacks in Wireless Ad Hoc Networks with lower communication and memory overhead.