Fuzzy Based Secure Clustering Schemes for Wireless Sensor Networks

This dissertation presents three independent novel approaches for distinct scenarios to solve one or more open challenges. The first concern explains the focus on the lifetime of the networks: this dissertation will utilize a fuzzy logic-based clustering protocol with multi-hop transmission for load balancing, energy consumption minimization, and network lifetime prolongation. The protocol forms unequal clusters with cluster head (CH) being selected by fuzzy logic with competition radius. Node distance to the base station, concentration, and residual energy are input variables. The second concern focuses on network stability: we design a type 2 fuzzy logic-based clustering schemes in a multi-hop WSN to reduce energy consumption and improve network scalability. In this clustering scheme, we propose a cluster head (CH) selection strategy where a sensor node is elected as a CH based on type 2 fuzzy logic inputs. To balance the load of CHs we also select their radius size based on the fuzzy logic inputs. Finally, the third concern is focus on the utility of game theory in defensive Wireless Sensor Networks (WSN) from selfish nodes and malicious behavior. Game theory can effectively model WSNs malicious attacks because of their low complexity and scalability. The study, thus, explores different WSN defense strategies from both external attackers and internal nodes acting selfishly or maliciously using the game theory approach. Also, the chapter highlights the general trust model for decision-making using the game theory framework. Besides, the chapter demonstrates the significance of the theory in ensuring WSN security from acute attacks and its role in enhancing trustworthiness in data and cooperation of nodes in various WSN architectures.