Preserving Privacy of Finite Impulse Response Systems

Abstract

Adding input and output noises for increasing model identification error of finite impulse response (FIR) systems is considered. This is motivated by the desire to protect the model of the system as a trade secret by rendering model identification techniques ineffective. Optimal filters for constructing additive noises that maximizes the identification error subject to maintaining the closed-loop performance degradation below a limit are constructed. Furthermore, differential privacy is used for designing output noises that preserve the privacy of the model.