Proceedings of the 15th ACM International Symposium on QoS and Security for Wireless and Mobile Networks | 2019
Countering Data and Control Plane Attack On OLSR Using Passive Neighbor Policing and Inconsistency Identification
Abstract
In this paper, we perform a comprehensive analysis on different types of blackhole attacks on MANETs and investigate the impact of these attacks on both Data and Control planes of the OLSR routing protocol. Our proposed models called Neighbor Watch Model (NWM) and Inconsistency Measurement Model (IMM), empowers each node to depend on itself to identify and isolate malicious nodes. We utilized the concept of passive neighbor watching (local vigilance) for NWM and introduced inconsistency identification mechanism for IMM. We design two different versions of both model, namely Local-NWM/IMM and Global-NWM/IMM, and utilize them against five major blackhole attack scenarios possible in a MANET with OLSR as the routing protocol. Our model reduces the impact of malicious nodes in the network and identifies/isolates such nodes by feeding correct link state information to OLSR continuously, without introducing any redundancy. We evaluate the performance of our models by emulating network scenarios in Common Open Research Emulator (CORE) for static as well as dynamic topologies. From our findings, it is observed that both proposed models greatly mitigate the impact of data and control blackhole attacks under all attack scenarios and improves the packet delivery performance of OLSR. Global-NWM/IMM performs much better than Local-NWM/IMM, but requires some modifications to OLSR.