Privacy Preserving Detection of Patterns in Event Sequences

We propose to use pattern matching on data streams from sensors in order to monitor and detect events of interest. We consider a privacy preserving pattern matching problem where patterns are given as sequences of constraints on input elements. We describe a new privacy preserving pattern matching algorithm over an infinite alphabet A where a pattern P is given as a sequence {p_{i 1}, p_{i 2},..., p_{i m}} of predicates pi_j defined on A. The algorithm address 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 p_i(e_j) privately, that is, sensors will not need to disclose the measurements x_i ^(j), x₂ ^(j),..., x_n ^(j) to the evaluator.