Malicious Nodes Detection in MANET Using Back-Off Clustering Approach

Abstract

Mobile Ad hoc Networks (MANET) are infrastructure less networks which provide multi-hop wireless links between nodes. The main applications of MANET in real time environment are military and emergency areas where the fixed infrastructure is not required. It is a temporary communication infrastructure network for quick communication with minimal configuration settings among the group of nodes. The security is one of the primary concerns in MANET. The malicious nodes in MANET environment degrade the performance of the network. In this paper, the nodes in MANET are grouped using back-off duration technique and further the malicious nodes are detected using this algorithm. The proposed clustering based malicious nodes detection in MANET achieves higher performance in terms of packet delivery ratio, latency and energy consumption. The proposed method achieves 89.35% of packet delivery ratio, 36.2 ms latency and 26.91 mJ of energy consumption.

Intelligent Intrusion Detection Techniques for Secure Communications in Wireless Networks: A Survey

“…From Figure 1, it can be observed that the performance of the system which is proposed by Rajeswari et al (2016) is better when it is compared with other existing systems. Which system used soft computing techniques such as neural network, genetic algorithm and fuzzy logic achieved better accuracy than other systems.…”

“…Ganapathy et al (2016) proposed a new IDS with the combination of the Intelligent CRF-based feature selection and the layered approach for effective intrusion detection. Rajeswari et al (2016) proposed a new IDS for detecting malicious nodes in MANETs using backoff clustering method. The advantage of their system is to identify, detect and prevent the novel attacks effectively.…”

“…They achieved very less detection accuracies only in all types of attacks specially U2R and R2L. Rajeswari et al (2016) proposed a new system for detecting malicious nodes in MANET. Authors did not use any soft computing approaches for making effective decisions over cluster head selection and attacks.…”