Open AccessPRIVACY PRESERVING PATTERN MATCHING ON SEQUENCES OF EVENTS
Author(s) -
Vladimir Oleshchuk
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.4.3.367
Subject(s) - pattern matching , sequence (biology) , matching (statistics) , alphabet , computer science , context (archaeology) , order (exchange) , algorithm , data mining , theoretical computer science , pattern recognition (psychology) , mathematics , artificial intelligence , statistics , paleontology , linguistics , genetics , philosophy , finance , economics , biology
We propose to 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 specified as sequences of constraints on input elements. We propose a new privacy preserving pattern matching algorithm over an infinite alphabet A where a pattern P is given as a sequence { pi , pi ,..., pim } 1 2 of predicates pi j defined on A . The algorithm addresses the following problem: given a pattern P and an input sequence t, find privately all positions i 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 measurements ( ) ( ) ( j )