Abstract
Sensor networks have been widely employed in many real-time applications. One of the most obvious challenges appearing to threaten the successful deployment of sensor networks is privacy issues including source-location privacy which cannot be adequately addressed by general security mechanisms. Focusing on this important kind of privacy, among many approaches proposed in literatures, self-adjusting phantom routing is a very successful one. But it still has some weaknesses. In this paper, we propose an improved version of it to enhance its performance. This method can decrease energy consumption and communication cost while increase the accuracy of the aggregate locations by minimizing their monitored areas.
Highlights
As a cost-efficient approach for collecting real time data, sensor networks have been widely employed in many monitoring-based applications such as gathering data regarding highway traffic, battle field reconnaissance, and habit monitoring of endangered animal species
One of most obvious challenges appearing to threaten the successful deployment of sensor networks is the concern of privacy issues [2]
Achieving privacy in sensor networks is a complicated problem by the fact that sensor networks normally consist of a set of low-cost radio devices that operate on readily-available, standardized wireless communication technologies [4,5,6]
Summary
As a cost-efficient approach for collecting real time data, sensor networks have been widely employed in many monitoring-based applications such as gathering data regarding highway traffic, battle field reconnaissance, and habit monitoring of endangered animal species. A number of augmenting methods, known as fake source messaging in [1], phantom routing in [2], and self-adjusting phantom routing in [3], have been proposed to be combined with the existing popular routing protocols to achieve source-location privacy in sensor network. To preserve personal location privacy, we propose two in-network aggregate location anonymization algorithms, namely, resource- and quality-aware algorithms Both algorithms require the sensor nodes to collaborate with each other to blur their sensing areas into cloaked areas, such that each cloaked area contains at least k persons to constitute a k-anonymous cloaked area. A will be iteratively refined based on extra communication among the sensor nodes until its area reaches the minimal possible size For both algorithms, the sensor node reports its cloaked area with the number of monitored persons in the area as an aggregate location to the server.
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