Wireless sensor networks (WSNs) as an emerging technology faces numerous challenges. Sensor nodes are usually resource constrained. Sensor nodes are also vulnerable to physical attacks or node compromises. Answering queries over data is one of the basic functionalities of WSNs. Both resource constraints and security issues make designing mechanisms for data aggregation particularly challenging. In this thesis, we first explore the various security techniques for data aggregation in WSNs then we design and demonstrate the feasibility of an innovative reputation-based framework rooted in rigorous statistical theory and belief theory to characterize the trustworthiness of individual nodes and data queries in WSNs.
Detecting security vulnerabilities is an imperative task. Visualization techniques have been developed over decades and are powerful when employed in the field of network security. In this thesis, we present a novel security visualization tool called “SecVizer”.