E-IASAODV: an enhanced framework for preventing Ad-hoc on-demand Distance Vector (AODV) multiple black hole attack in MANET

Abstract

Mobile Ad-hoc networks (MANETS) are collection of mobile nodes that dynamically change the network topology in which nodes can join and leave the network at any point of time. Due to fundamental characteristics of MANETS, such as open medium, dynamic topology, and distributed cooperation; it creates several security vulnerabilities to its security design. Security is an essential requirement in mobile Ad-hoc networks to provide secure communication between mobile nodes. Ad-Hoc On-demand Distance Vector (AODV) routing protocol is a routing protocol in MANET that broadcast the network with a route discovery message anytime a node is seeking for a route to a destination, any node that have a route to that destination will reply to the route discovery request, which provides a vulnerability to the routing protocol by making it open to black hole attack which is one of the most common attacks in MANETs. A Black Hole is a malicious node that falsely replies to any route requests without having active route to specified destination and drops all received packets. This work, which is an enhancement of Intrusion Avoidance System for Ad-Hoc on-demand Distance Vector (IASAODV), a framework developed in 2015 to prevent black hole attack, presents a new framework that prevents the security threats of AODV multiple Black Hole attack with better Packet Delivery Ratio (PDR). This framework tackled the problem by making nodes monitor the activities of their neighbors by collecting Route Request (RREQ) messages sent by nodes and keeping in a table. To justify the solution, we made appropriate implementation and simulation using Network Simulator NS-2.35. The conducted experimental result shows an improvement in Packet Delivery Ratio (PDR) compared to that of IASAODV routing Protocol with the proposed framework having 100%, 100%, 99% and 98% for 1, 3, 5 and 7 malicious nodes respectively compared to the existing system with 88%, 79%, 61% and 57%, for 1,3,5 and 7 malicious nodes respectively

Keywords: MANETs, AODV, IASAODV, RREQ, RREP, NS2, HRRT