Privacy Preserving Monitoring and Surveillance in Sensor Networks

Abstract

In this paper we consider a problem of privacy preserving surveillance and monitoring in sensor networks. We propose a framework and a solution of the problem based on multi-party computations. Our approach use pattern matching on data streams from sensors in order to monitor and detect events of interest. We study a privacy preserving pattern matching problem where patterns are defined as sequences of constraints on input data items. We describe a new privacy preserving pattern matching algorithm over an infinite alphabet A where a pattern P is given as a sequence {pi1, pi2, ..., pin} of predicates pij defined on A. The algorithm addresses the following problem: given a pattern P and an input sequence t, find privately all positions in t where P matches t. The privacy preserving in the context of this paper means that sensor measurements will be evaluated as predicates pi(ej) privately, that is, sensors will not need to disclose the measurement values to the monitor.