# Preserving Privacy of Finite Impulse Response Systems

## TL;DR

This paper proposes methods to add noise to FIR systems to protect their models from identification, balancing privacy with system performance, using optimal filtering and differential privacy techniques.

## Contribution

It introduces novel noise design strategies for FIR systems that maximize identification error while controlling performance loss, combining optimal filtering and differential privacy.

## Key findings

- Optimal filters for noise construction are developed.
- Differential privacy mechanisms are applied to FIR systems.
- Trade-offs between privacy and system performance are characterized.

## 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.