arrow
Return

A Polynomial-Time Algorithm for the Secure State Estimation Problem Under Sparse Sensor Attacks via State Decomposition Technique

delete2023-12-01
delete9
PRE
AI
A
An‐Yang Lu
G
Guang‐Hong Yang *
DOI:10.1109/TAC.2023.3278839delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This article investigates the secure state estimation problem for cyber-physical systems (CPSs) under sparse sensor attacks. In the existing results, the secure state estimation is usually established as an NP-hard problem where combinatorial candidates should be checked since the set of attacked channels is unknown. For avoiding brute force search, a novel state decomposition technique is proposed such that the state can be reconstructed by a simple majority vote. Necessary and sufficient conditions for the observability of the decomposition elements are given, and based on the obtained conditions, an effective for designing the decomposition matrix is also proposed. Then, a polynomial-time secure state estimation strategy is constructed based on the proposed state decomposition technique. It is shown that besides 2 s-sparse eigenvalue observable systems, the secure state estimation problem can be solved in polynomial time for more general cases where each decomposition element is B-observable for at least 2s+1 sensors. Finally, the effectiveness of the proposed methods is demonstrated by two simulations showing the decrease of computational complexity and the effectiveness under different cases.
Keywords:
Cyber-physical systems (CPSs)
polynomial-time
secure state estimation
sparse sensor attack
state decomposition technique

Journal

IEEE Transactions on Automatic Control cover
IEEE Transactions on Automatic Control
IF:
7
Papers:
1.3W
Citations:
6.7W

Organization

N
northeastern university - china
Scholars:
3.2W
Papers: 2.7W
Citations: 37
Cited Papers

Cited Papers

Various columnar phases formed by bent-core mesogens
err2003-10-01
err0
PREAI
errK. Pelz; W. Weissflog; U. Baumeister; S. Diele
errShare
errSave
err2023-02-01
err0
PREAI
err
errShare
errSave
errShare
errSave
researcher View more