Decentralized False-Data Injection Attacks Against State Omniscience: Existence and Security Analysis

Tian-Yu Zhang; Dan Ye; Yang Shi; Tianyu Zhang

doi:10.1109/TAC.2022.3209396

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Decentralized False-Data Injection Attacks Against State Omniscience: Existence and Security Analysis

Journal article

Peer reviewed

Decentralized False-Data Injection Attacks Against State Omniscience: Existence and Security Analysis

Tian-Yu Zhang, Dan Ye, Yang Shi and Tianyu Zhang

IEEE transactions on automatic control, Vol.68(8), pp.4634-4649

08/01/2023

DOI: 10.1109/TAC.2022.3209396

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Abstract

This article focuses on how false-data injection (FDI) attacks compromise state omniscience, which needs each node in a jointly detectable sensor network to estimate the entire plant state through distributed observers. To reveal the global vulnerability of state omniscience, we investigate decentralized FDI (DFDI) attacks that destabilize the estimation error dynamics but eliminate their influences on the residual in each sensor node. First, the sufficiency and necessity for the existence of such attacks are studied from system eigenvalues and attackable sensors. Second, the self-generated DFDI attack sequences independent of system real-time data are designed to achieve the attack objective with elaborate parameters. Especially, the DFDI attack sequences are improved to maintain real values even if the system matrix only has unstable imaginary eigenvalues. Finally, we analyze the secure range for observer interaction weights and the sensor protection scheme to guarantee the security of state omniscience under DFDI attacks. The theoretical results for DFDI attacks are demonstrated with the linearized discrete-time model of an aircraft system.

Complete stealthiness

cyber-physical system security

decentralized false-data injection (DFDI) attacks

Detectors

distributed observers

Eigenvalues and eigenfunctions

Estimation error

Kalman filters

Observers

Security

state omniscience

Wireless communication

Details

Title: Subtitle: Decentralized False-Data Injection Attacks Against State Omniscience: Existence and Security Analysis
Creators: Tian-Yu Zhang - College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning, China
Dan Ye - Northeastern University
Yang Shi - University of Victoria
Tianyu Zhang - Computer Science
Resource Type: Journal article
Publication Details: IEEE transactions on automatic control, Vol.68(8), pp.4634-4649
Publisher: IEEE
DOI: 10.1109/TAC.2022.3209396
ISSN: 0018-9286
eISSN: 1558-2523
Grant note: N2204008 / Fundamental Research Funds for the Central Universities (10.13039/501100012226) 62173071; U1813214; 61621004 / National Natural Science Foundation of China (10.13039/501100001809) XLYC1907035 / LiaoNing Revitalization Talents Program (10.13039/501100018617) 202062 / Liaoning BaiQianWan Talents Program BX20220061 / China Postdoctoral Science Foundation (10.13039/501100002858)
Language: English
Date published: 08/01/2023
Academic Unit: Computer Science
Record Identifier: 9984696718502771

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