Abstract

While many protocols for sensor network security provide confidentiality for the content of messages, contextual information usually remains exposed. Such information can be critical to the mission of the sensor network, such as the location of a target object in a monitoring application, and it is often important to protect this information as well as message content. There have been several recent studies on providing location privacy in sensor networks. However, these existing approaches assume a weak adversary model where the adversary sees only local network traffic. We first argue that a strong adversary model, the global eavesdropper, is often realistic in practice and can defeat existing techniques. We then formalize the location privacy issues under this strong adversary model and show how much communication overhead is needed for achieving a given level of privacy. We also propose two techniques that prevent the leakage of location information: periodic collection and source simulation. Periodic collection provides a high level of location privacy, while source simulation provides trade-offs between privacy, communication cost, and latency. Through analysis and simulation, we demonstrate that the proposed techniques are efficient and effective in protecting location information from the attacker.

While many protocols for sensor network security provide confidentiality for message content, contextual information generally remains exposed. Such contextual information can be exploited by an adversary to derive sensitive information such as the location of supervised objects and data sinks in the field. Attacks on these components can significantly undermine any network application. Existing techniques defend the leaking of location information from a limited adversary who can only observe network traffic in a small region. However, a stronger adversary, the spy of the world, is realistic and can defeat these existing techniques. This document first formalises the privacy issues of location on sensor networks under this strong adversary model and calculates a lower limit on the communication overhead required to reach a given level of site privacy. The paper proposes two techniques for providing location privacy to monitored objects (source privacy), and two techniques for providing location privacy to the data sinks (privacy of the sink location). These techniques provide interchanges between privacy, communication cost, and latency. Through analysis and simulation, demonstrate that the proposed techniques are efficient and effective for the source and privacy of sinks in sensor networks.

 A network of wireless sensors (WSN) usually comprises a large number of inexpensive sensors, self-organised as an ad hoc network to interact and study the physical world. Sensor networks can be used in applications where it is difficult or impossible to configure wired networks. Examples include target tracking, habitat monitoring, and military surveillance. These applications are subject to a variety of security problems in hostile environments. Most efforts to date in sensor network security have focused on providing classic security services such as confidentiality, authentication, integrity and availability. While these are critical requirements in many applications, they are not enough. The communication patterns of the sensors can, by themselves, expose a large amount of contextual information. For example, the delivery of sensor data to the base station may reveal the location of some critical events in the field, revealing valuable information. In hostile environments, it is particularly important to ensure the privacy of the location; Lack of location-based information protection can completely undermine network applications.