An Adaptive Fuzzy System based Insider Attacks detection with Group Key management for Wireless Ad-Hoc Network

Abstract

Abstract Ad-hoc networking of wireless devices permits the establishment of contact links on the taking part hubs without pre-arranged infrastructure. In wireless ad hoc networks, participatorynodestypicallyengageingroupcommunicationssuchasbroadcast, multi-accessor relay functions. Protecting these communications is a challenging task, as internal attackers may secretly cause damage to the network, which is difficult to predict. Internal attackers can affect the sensors negatively and may disrupt the network by dropping sensitive packets or modifying packet information maliciously. Inside attackers are capable of causing many types of activities as well as passive attacks. Attackers located at a critical point in the network can significantly affect network performance. Insider attackers conceal themselves by marking themselves as legitimate nodes. Therefore, it becomes hard for the system to differentiate dishonest nodes from honest nodes. So as to make the communication among the network more secure, an adaptive fuzzy system that uses CSO algorithm for selecting optimal membership function has been proposed. In this approach, the group key is distributed by the cluster head to the cluster members. This makes sure that only the nodes with the same group key can speak with one another. Implementing appropriate group-key management in the system that focuses on internal attacks identifies the dishonest nodes which can be then eliminated through some other security measures. This ensures the absence of the dishonest nodes inside the network. The results have been simulated and the execution of the proposed approach has been contrasted with the tradition FS approach. The results have shown the presented approach has performed better than the traditional approach.