An Attack Tree Based Risk Assessment for Location Privacy in Wireless Sensor Networks

The challenging nature of insecure wireless channels and constrained resources make protection for wireless sensor networks (WSNs) an especially essential problem. The existing work has focused on preventive techniques to achieve location privacy protection, while the location privacy risk assessment receives less attention. In this paper, we propose a novel risk assessment approach to evaluate the risk of WSNs privacy based on attack tree. Using the attack tree model, we can estimate the degree that a certain threat might bring to the WSNs and identify possible attack sequences that an attacker may launch towards the privacy preserving system in WSNs. Then we adopted the multi-attribute utility theory to calculate the system´s total risk value as well as the probabilities of each attack sequence. The analysis results can provide support for decision makers to make corresponding protection measures of location privacy．