Distributed Privacy-Preserving Fusion Estimation Using Homomorphic Encryption

Abstract

The privacy-preserving problem for distributed fusion estimation scheme is concerned in this paper. When legitimate user wants to obtain consistent information from multiple sensors, it always employs a fusion center (FC) to gather local data and compute distributed fusion estimates (DFEs). Due to the existence of potential eavesdropper, the data exchanged among sensors, FC and user imperatively require privacy preservation. Hence, we propose a distributed confidentiality fusion structure against eavesdropper by using Paillier homomorphic encryption approach. In this case, FC cannot acquire real values of local state estimates, while it only helps calculate encrypted DFEs. Then, the legitimate user can successfully obtain the true values of DFEs according to the encrypted information and secret keys, which is based on the homomorphism of encryption. Finally, an illustrative example is provided to verify the effectiveness of the proposed methods.

Keywords

eavesdropping attack / distributed fusion estimation (DFE) / homomorphic encryption / computational privacy