Isolating Misbehaving Nodes in MANETs with an Adaptive Trust Threshold Strategy

Abstract

Due to dynamic network topology, distributed architecture and absence of a centralized authority, Mobile Ad hoc Networks (MANETs) are vulnerable to various attacks from misbehaving nodes. To enhance the security of MANETs, various trust-based schemes have been proposed that augment the traditional cryptography-based security schemes. However, most of these schemes use static and predefined trust thresholds for node misbehavior detection, without taking into consideration the network conditions locally at each node. Using static trust thresholds for misbehavior detection may result in high false positives, low malicious node detection rate, and network partitioning. In this paper, we propose a novel Adaptive Trust Threshold (ATT) strategy that adapts the trust threshold in the routing protocol according to the network conditions such as rate of link changes, node degree and connectivity, and average neighborhood trustworthiness. We identify the topology factors that affect the trust threshold at each node, and leverage them to build a mathematical model for ATT computation. We compare our ATT strategy with one of the most recently proposed trust-based security schemes. Our simulation results indicate that the ATT strategy is robust in terms of convergence to the same trust threshold value computed at all neighbor nodes for malicious nodes and is energy efficient. Moreover, the ATT strategy achieves significant improvements in packet delivery ratio, reduction in false positives, and increase in detection rate as compared to non-ATT schemes (static trust threshold based schemes).