For sensor networks deployed to monitor and report real events, event source location privacy is an attractive and critical security property, which unfortunately is also very difficult and expensive to achieve. This is not only because adversaries may attack against sensor source privacy through traffic analysis, but also because sensor networks are very limited in resources. In this talk, we will discuss the techniques we have developed for enhancing source location privacy in sensor networks under a global adversarial model. Specifically, we will propose the notion of statistically strong source anonymity, where carefully chosen dummy traffic will be introduced to hide the real event sources. In addition, several privacy-preserving mechanisms will be employed to drop dummy messages on their roads to the base station to prevent explosion of network traffic.