Wireless sensors networks(WSNs) consists of large number of tiny sensors having the capabilities of sensing, processing and communication, being a vital part of many incredible applications that mostly including monitoring and tracking activities,, have been attracted attention of many researchers.  In order to carry out these applications successfully, the Wireless sensors networks (WSNs) can be seen in many different forms ranges from small to large scale distributed wireless sensor networks in hostile environments. Therefore, researchers especially focused for efficient  and careful design of these networks in order to get better results for WSNs oriented applications. 

One of such attempt from research community can be seen in the form of hierarchical structuring or clustering algorithms for this large scale distributed wireless sensor networks for efficient utilization of limited resources at nodes and overcoming the various challenges that results from it. Thus, cluster based wireless sensor network (CBWSNs) have the capability to elevate the related problems of resource limitation of nodes while performing their basic activities i.e. routing, aggregating and forwarding their sensed data to the destination. On the other hand, the security is become a great concern, when the nodes inside the cluster compromised and start misbehaving in order to save their limited resources for their own use. Such attacks are known as internal attacks or passive attacks. At present, the existing security measures for WSNs cannot ensure that these problems will not be launched. Therefore, it is important to protect the CBWSNs from internal attacks, which is the main goal of this thesis.

However, the security becomes a big problem for CBWSNs, especially when nodes in the cluster selfishly behave, e.g., not forwarding other nodes’ data, to save their limited resources. This may make the cluster obsolete, even destroying the network. Thus, a way to guarantee the secure and consistent clusters is needed for proper working of CBWSNs. We showed that the selfishness attack, i. e. passive attack or insider attack, in CBWSNs can cause severe performance disaster, when particularly a cluster head node becomes selfish. In order to prevent this situation, we proposed a security framework that involves a novel clustering technique as well as a reputation system at nodes for controlling selfishness, making them cooperative and honest. The novelty of the clustering comes from the existence of inspector node (IN) to monitor the cluster head (CH) and its special working style. Later on, modified version of this security framework changed the clustering criteria and as well as using the reputation system based on data mining for more efficient controlling of the selfishness problem. The experimental results showed that the proposed security framework can control the selfishness and thus improve the security of the clusters.