An improved model based on genetic algorithm for detecting intrusion in mobile ad hoc network

Abstract

In any data communication between networks, it is very essential to maintain a high level of security to make sure that the data communication is safe and trusted. There may be chance for intrusions and misuses of information in a network. Intrusion detection systems (IDSs) has become an important component in terms of computer and network security. Detection can be host based or network based. The existing approaches being utilized in intrusion detection are not efficient. This paper presents a genetic algorithm based IDS to detect the malicious nodes in the network. Cloud computing understands users in network nodes in ad hoc or fixed manner to have long term connectivity for service utilization. The proposed approach performs better compared to Gaussian Naive Bayes classifier approach. The objective value of chromosome is calculated through a set of iterations. The experimental results show that the computation time is reduced with high successful detection and network performance is improved to provide reliable transmission. The model is also suitable for users on cloud framework.