Social and QoS based trust model for secure clustering for wireless body area network

Abstract

Wireless Body Area Networks (WBAN) is an emerging technology, a subset of Wireless Sensor Network. WBAN is a collection of pieces of tiny wireless body sensors with small computational capability and communicates short distance using ZigBee or Bluetooth. The main application of WBAN is in healthcare industry like remote patient monitoring. The small pieces of sensor monitor health factors like body temperature, pulse rate, ECG, heart rate etc., and communicate it to the base station or central coordinator for aggregation or for data computation. The final data is communicated to remote monitoring devices through internet or cloud service providers. The main challenge of this technology is dead nodes due to high energy consumption with all the wireless node working on battery. Minimization of the energy consumption extends life of the network. Security is another major challenge. There are possibilities of internal attacks being executed by malicious nodes, creating problems for the network. This paper proposes a model which provides solution for extending the life span of the network by minimizing energy consumption and also proposes model to provide solution for internal soft attacks created within the network through calculation or trust, computation among nodes to identify malicious nodes with the help of social-and QoS-based trust computation for secure clustering and communication. The proposed model is compared with LEACH and LEACH-MM protocol and performance is measured with various parameters.