Srinivasan, Avinash.

This dissertation presents the results of research that led to the development of a novel reputation and trust-based monitoring paradigm for secure and reliable computing in Wireless Sensor Networks (WSNs). WSNs have undergone tremendous technological advances over the last few years. They have caused a giant leap toward "proactive computing," a paradigm where computers anticipate human needs and, when necessary, act on their behalf. Therefore, we cannot deploy such a critical technology without first addressing the security and privacy challenges to ensure that it does not turn against those whom it is meant to benefit. The core application of WSNs is to detect and report events, be it military or civilian applications. The building blocks of a WSN are small, battery-powered, lowcost, self-contained devices called "sensors" that measure factors like light, temperature, pressure, vibration, motion, etc. A WSN usually consists of hundreds of thousands of sensors that operate in unattended, hostile territories to monitor a given geographical area. Once deployed, the wireless sensors self-organize into ad-hoc wireless networks in order to cope with the dynamics of the surveillance field. During the post deployment phase, the wireless sensors aggregate data, then process and generate a report, which is subsequently relayed from one sensor to the next using secure multi-hop routing until the data reaches its desired destination, which is usually the sink. Since sensors operate in unattended and hostile territories, the adversary can capture a sensor node physically and extract all the information stored onboard, including cryptographic keying material. With this unique situation, WSNs are subject to a unique attack referred to as an "Insider Attack," in which the adversary becomes a legitimate member of the network being represented by the captured node.