A Machine Learning Method For Sensor Authentication Using Hidden Markov Models

Abstract

A machine learning method for sensor based authentication is presented. It exploits hidden markov models to generate stable and synthetic probability density functions from variant sensor data. The principle, and novelty, of the new method are presented in detail together with a statistical evaluation. The results show a marked improvement in stability through the use of hidden markov models.