Game Theory Approach on Security Strategy in Wireless Sensor Networks

Abstract

Wireless Sensor Networks has become a phenomenon in the recent developments and convergences in the technology of microelectronic devices, integrated circuit architectures, microprocessor hardware, nanotechnology, wireless connectivity, ad-hoc networking, distributed signal treatment, and embedded systems (WSNs). The abilities of sensor nodes are limited in terms of electricity supply, restricted computing power, and communication bandwidth. However, the routing protocols have been paid the most attention because they could vary according to the application and the network architecture. The design of effective routing protocols is essential to extend the life of the sensor nodes. Although sensors are primarily designed to track and record incidents, as they rely on the application, a single routing protocol for sensor networks in all applications may not be efficient. On the other hand, providing better QoS and secure communication is also an important field of research. In this work, we focus on WSN and study various aspects of WSN, such as secure communication, better QoS, and routing schemes. We have different aggregation and protection routing mechanisms to deal with these problems. First, we concentrated on the data aggregation method in WSN. We developed a new strategy for enhancing network lifetime using a proposed solution based on the fuzzy logic framework called the Energy-Aware Fuzzy Logic Secure Data Aggregation (EA-FSDA). We also offer a privacy safeguard framework to enhance reliability for the stable aggregation of data. The method for privacy conservation is developed using homomorphic data encryption. Therefore, the approach suggested offers a solution that can boost the network's overall efficiency for the effective and stable aggregation of WSN data. We concentrated on choosing and routing energy-conscious cluster heads to improve the network lifetime. In order to do this, we are presenting the merged model using Particle Swarm Optimization (PSO) and Gravitational Search Algorithm (GSA) for choosing cluster heads. Finally, for stable data aggregation, we implement a game theory-based trust management platform and the key distribution model. The AES encryption-based scheme is often used to protect data during two or more hops communications. The comparative analysis shows that the suggested solution decreases response time, uses fewer resources, and reduces total network delays.