Human immune-based model for intrusion detection in mobile ad hoc networks

Abstract

Mobile ad hoc network (MANET) is a collection of mobile, decentralized and self-organizing nodes that are used in special cases such as medical and military purposes. Securing mobile ad hoc network MANET is a crucial research issue. The properties of MANET impede the protection of the network’s environment against attacks. MANET as an open area of wireless mobile nodes allow external attackers to join the network easily and masquerade legitimate nodes. Therefore, the objective of this paper is to develop a distributed, self-organizing and hybrid intelligent model, called dendritic cell fuzzy algorithm (DCFA), for security routing in MANET. The DCFA model inspiring the detection functionality of dendritic cells (DCs) in human immune system (HIS) and the accurate decision-making functionality of fuzzy logic theory to detect network attacks in MANET. The DCFA model is developed and validated by detecting a flooding-based attack, namely, a resource consumption attack (RCA). QualNet v5.0.2 is used as a simulation environment to test the capability of DCFA in detecting RCA over MANET. The results show the capability of DCFA to perform the detection operation with high efficiency and effectiveness.