Accurate and Cognitive Intrusion Detection System (ACIDS): a Novel Black Hole Detection Mechanism in Mobile Ad Hoc Networks

Abstract

Mobile Ad-hoc Network (MANETs) is infrastructure less in nature as it is encompassed with a collection of mobile nodes. The self-configurable feature of it has proven to be beneficial in times of disaster relief and rescue operations as the mobile nodes can be effortlessly deployed regardless of the geographical location. In this network, communication take place with the aid of several cooperative routing protocols such as AODV, DSDV, DSR etc., Due to the lack of a centralized administration, the network is prone to copious routing attacks. In this paper, an intrusion detection system called ‘Accurate and Cognitive Intrusion Detection System’ (ACIDS) for detecting the most vulnerable packet dropping attack known as black hole attack has been developed. This system takes the parameters such as Destination Sequence Number (DSN) and Route Reply (RREP) into consideration for detecting the intruders by identifying the deviation of the chosen parameters from the normal behavior. The proposed system has been simulated using NS2 and the analysis of the results attest to the efficacy of ACIDS over AODV routing protocol in detecting packet dropping scenarios of the black hole attack.