A dynamic fuzzy commitment scheme using ARRSES forecasting

Abstract

A dynamic fuzzy commitment scheme gradually changes its stored commitment by the time while retains the fuzzy authentication behavior. When an entry passes the authentication, its value is taken to update the commitment. In this paper, we propose simplified Adaptive Response Rate Single Exponential Smoothing (ARRSES) which can be used to forecast the next commitment by using the authenticated input together with the existing commitment. The dynamic fuzzy commitment scheme using ARRSES forecasting stores only one commitment. We have the value of smoothing constant adjusted according to the characteristics of the data. The optimal beta is recommended to achieve the highest successful authentication rate. © 2012 Infonomics Society.