Detection of selfish attack over wireless body area networks

Abstract

Wireless sensor network (WSN) is the promising technology that is being used for several applications in multiple fields. Advancements of WSN have made it possible to deploy the sensors in the several fields (e.g. battle, environmentmonitoring, surveillance, industry, health etc.) However, existing approaches experience the severe security threats in the field of WSNs particularly in the wireless body area networks (WBANs). These security threats are observed at the all layers. However, Medium Access Control (MAC) sub-layer faces more challenges as compared with other layers because of radio that consumes more energy resources. Thus, any possible attack over the MAC makes the slow down working process of WBANs. There are several well-known attacks that cause the additional energy consumption observed at the MAC layer in WBANs. These attacks involve the collision, denial of sleep, and selfish attack. The collision attack and denial of sleep attacks are researched and handled for MAC over the WBANs. However, selfish attack is not properly addressed. In this paper, we propose a selfish detection medium access control (SDMAC) algorithm against selfish attack in WBAN. Here the adversary nodes have advantage over legitimate nodes on MAC protocols that uses the resources wrongly, which leads to energy consumption in sensor nodes, proposed algorithm detects the fake node and blocks the unusual activities. In this case, network performance is improved after applying this proposed algorithm. To validate the performance of the proposed algorithm, the simulation is conducted using NS3. Based on the simulation results, we demonstrate that our proposed SDMAC outperforms other known existing protocols from energy efficiency and bandwidth reduction perspective.