Enhanced Detection and Recovery from Flooding Attack in MANETs using AODV Routing Protocol

Abstract

Mobile ad-hoc network (MANET) is a self-deliberate data network, where all nodes behave like host or router. MANET is a collection of number of mobile nodes or devices that randomly generate a temporary network. Security is the fundamental requirement in MANET due to its behavior of changing topology, open medium and lack of centralized authentication. This leads to various security attacks in mobile ad hoc network and violate the criteria of routing mechanism. Mobile Ad-hoc network doesn't need backbone infrastructure support and it is very reliable and also contains the routable networking environment. In this paper, the effect of flooding attack in AODV based network is explained. The network parameters like Throughput, Packet Delivery Fraction (PDF) and End to End Delay are compared with normal network (without flooding attack) and a network with one or more flooder nodes. The performance of network parameters is compared in all the three scenarios. We have proposed a scheme which is finds single or number of malicious nodes in the network and drops fake packets.

Avoiding and Isolating Flooding Attack by Enhancing AODV MANET Protocol (AIF_AODV)

“…We implemented AIF AODV in different scenarios in order to compare it with the two other proposed models [9,14] from the related work section.…”

“…Out of this comparison, we can see the ability of AIF AODV to resist multiple flooding attacker nodes in the same network. We compared the overall performance of AIF AODV with the proposed model in [14], which we called EDR (Enhanced Detection and Recovery), in terms of Throughput and PDR. The number of nodes increases from 25 to 100 nodes, the terrain coordination is 500x500 m, and the speed of nodes is 3 mps (low mobility scenario).…”

“…Shruti Bhalodiya et al [14] proposed a schema to detect the RREQ Flooding attack in MANET. The proposed schema uses a filtering technique to check the RREQ RATELIMIT for every node.…”

“…The limitation in [8,14] is that they depend on a static value as a threshold to detect the attacker node in the network, which should be a dynamic value. The limitation in [8,12,13,17] is that an alarm message is broadcasted to normal nodes after the detection of an attacker node in the If the requesting node is in the suspicious list and it broadcasts requests for different IDs then add requester node ID to the black list If the requesting node is not in the suspicious list and it broadcasts requests for different IDs then add requester node ID to the suspicious list network, which makes the network vulnerable to a blackmail attack because a blackmail attacker node can broadcast false alarm messages containing normal nodes IDs to isolate them from other normal nodes in the network.…”

DDoS Attack and Detection Methods in Internet-Enabled Networks: Concept, Research Perspectives, and Challenges

“…Meanwhile, compared with the greedy algorithm, the flight path of the UAVs is reduced by 15.44%. In [73], a threshold-based detection scheme was proposed to detect RREQ flooding attacks in mobile ad hoc networks (MANET). In this study, the throughput, packet delivery fraction, and end-to-end delay of network traffic were compared with legitimate network traffic (without flooding attacks) and a network with one or more flooder nodes.…”