Distributed filtering algorithm based on local outlier factor under data integrity attacks *

Yue Luo

doi:10.1016/j.jfranklin.2022.12.047

Distributed filtering algorithm based on local outlier factor under data integrity attacks *

2023-08-01

3

PRE

AI

DOI：10.1016/j.jfranklin.2022.12.047

Original

Original request for help

Save

Abstract

En 中文

Network security is becoming a prominent issue for the development of information technology, and intelligent network attacks pose great challenges to system security due to its strong concealment. The existence of these attacks threatens the operation process of the complicated control system. Motivated by such a security problem, we study the secure distributed filtering algorithm under a kind of complex data integrity attack which can attack in two forms. We design a detection mechanism based on local outlier factor to distinguish the rightness of exchanged data, which determines whether to fuse the estimates by comparing the local density (LD) of the estimation of each sensor. Such a detection mechanism does not need the sensor to transmit redundant data information, thus greatly saving calculation cost and improving transmission efficiency. Meanwhile, we optimize the distributed filtering algorithm and obtain a suboptimal estimation gain. Finally, we demonstrate a numerical example to verify the availability of the filtering algorithm, and explore the influence of detector parameters on the performance of the estimation system. & COPY; 2023 The Franklin Institute. Published by Elsevier Inc. All rights reserved.

Keywords:

STATE ESTIMATION

ONLINE DETECTION

SYSTEMS

Distributed filtering algorithm based on local outlier factor under data integrity attacks *

Abstract

Journal

Organization