MMSE estimation in a sensor network in the presence of an adversary

Abstract

Estimation in a two node sensor network is considered, with one sensor of high quality but potentially affected by an adversary and one sensor of low quality but immune to the actions of the adversary. The observations of the sensors are combined at a fusion center to produce a minimum mean square error (MSE) estimate taking into account the actions of the adversary. An approach based on hypothesis testing is introduced to decide whether the high quality sensor should be used. The false alarm probability of the hypothesis test introduces a natural trade-off between the MSE performance when the adversary takes no action and when the adversary acts. Finally, a method is developed to select the false alarm probability robustly to ensure good performance regardless of the adversary's action.