Adaptive-Width Generalized Correntropy Diffusion Algorithm for Secure Distributed Estimation
Hadi Zayyani, Mehdi Korki
Abstract
In this brief, a secure distributed estimation algorithm is devised, based on a generalized correntropy kernel function, which is robust against malicious attacks with false data injection model. An adaptive-width mechanism of generalized correntropy is suggested to reduce the effect of the adversaries in the network by narrowing the width of the generalized correntropy. This makes the proposed distributed algorithm be robust against false data injection attackers. Moreover, some analysis such as updating the parameter width and determining the optimal threshold for adversary detection are provided. Simulation results show the effectiveness of the proposed secure distributed estimation algorithm in comparison with some state-of-the-art algorithms in the literature and also demonstrate the effective detection capability of the adversary.