Sensor networks will be deployed everywhere around us, e.g., in offices and residential houses. There are many concerns related to privacy in this scenario because people and their activities will be monitored all the time. For example, data collected for temperature monitoring in an office should not be used to imply the presence of a person, which is a private information; unauthorized person should not be allowed to access the sensed data that is privacy-sensitive. To make the sensor network deployment more realistic in our daily life, it is imperative to consider the privacy concerns in sensor networks.
This project aims to build a privacy-preserving infrastructure for sensor networks. It considers the privacy breaches due to the information leakage to (1) untrusted sensor networks, (2) untrusted users, and (3) outside observers. In the context of the three adversary models, this project focuses on the most important operations in sensor networks: data query, data sharing, and data routing. Specifically, the problems addressed in the project include how to store data or aggregate data so that data query can be responded in a privacy-preserving fashion, how to provide security primitives to prevent unauthorized users from accessing collected data, and how to design routing algorithms to preserve location privacy.
The research conducted in this project is expected to deepen our understanding in building a privacy preserving sensor network, and provide a realistic implementation suite for security and privacy support for sensor networks.
