Abstract—Mobile Ad Hoc Networks (MANETs) form a promising approach for applications that need fast installation with no infrastructure especially in disaster recovery and emergency operations. However, many challenges are facing MANETs including security, routing, transmission range and dynamically changing topology with high nodes mobility. Security is considered as the main obstacle for the widespread adoption of MANET applications. Black hole attack is a type of DoS attack that can disrupt the services of the network layer. It has the worst malicious impact on network performance as the number of malicious nodes increases. Several mechanisms and protocols have been proposed to detect and mitigate its effects using different strategies. However, many of these solutions impose more overhead and increase the average end-to-end delay. This paper proposes an enhanced and modified mechanism called "Enhanced RID-AODV", based on a preceding mechanism: RID-AODV. The proposed enhancement is based on creating dynamic blacklists for each node in the network. Each node, according to criteria depends on the number of mismatches of hash values of received packets as compared with some threshold values, can decide to add or remove other nodes to or from its blacklist. The threshold is a function of mobility (variable threshold) to cancel the effect of normal link failure. Enhanced RID-AODV was implemented in ns-2 simulator and compared with three previous solutions for mitigating multiple black hole attacks in terms of performance metrics. The results show an increase in throughput and packet delivery ratio and a decrease in end-to-end delay and overhead ratio.
Index Terms—Enhanced RID-AODV, MANET security, multiple black hole attacks, network layer attack.
The authors are with the Computer Engineering Department at Al-Quds University in Jerusalem, Palestine (e-mail: rhamamreh@eng.alquds.edu, asalem@outlook.com).
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Cite:Rushdi A. Hamamreh and Abdul-Rahman Salem, "Protocol to Avoid Multiple Black Hole Attacks in MANETs," Journal of Advances in Computer Networks vol. 4, no. 3, pp. 161-166, 2016.