dc.contributor.author | Mousavinejad, Eman | |
dc.contributor.author | Yang, Fuwen | |
dc.contributor.author | Han, Qing-Long | |
dc.contributor.author | Vlacic, Ljubo | |
dc.date.accessioned | 2019-07-04T12:31:13Z | |
dc.date.available | 2019-07-04T12:31:13Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 2168-2267 | |
dc.identifier.doi | 10.1109/TCYB.2018.2843358 | |
dc.identifier.uri | http://hdl.handle.net/10072/380049 | |
dc.description.abstract | This paper is concerned with cyber attack detection in a networked control system. A novel cyber attack detection method, which consists of two steps: 1) a prediction step and 2) a measurement update step, is developed. An estimation ellipsoid set is calculated through updating the prediction ellipsoid set with the current sensor measurement data. Based on the intersection between these two ellipsoid sets, two criteria are provided to detect cyber attacks injecting malicious signals into physical components (i.e., sensors and actuators) or into a communication network through which information among physical components is transmitted. There exists a cyber attack on sensors or a network exchanging data between sensors and controllers if there is no intersection between the prediction set and the estimation set updated at the current time instant. Actuators or network transmitting data between controllers and actuators are under a cyber attack if the prediction set has no intersection with the estimation set updated at the previous time instant. Recursive algorithms for the calculation of the two ellipsoid sets and for the attack detection on physical components and the communication network are proposed. Simulation results for two types of cyber attacks, namely a replay attack and a bias injection attack, are provided to demonstrate the effectiveness of the proposed method. | |
dc.description.peerreviewed | Yes | |
dc.description.sponsorship | Swinburne University of Technology ARC | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | IEEE | |
dc.publisher.place | United States | |
dc.relation.ispartofpagefrom | 1 | |
dc.relation.ispartofpageto | 11 | |
dc.relation.ispartofjournal | IEEE Transactions on Cybernetics | |
dc.relation.uri | http://purl.org/au-research/grants/ARC/DP160103567 | |
dc.relation.grantID | DP160103567 | |
dc.relation.funders | ARC | |
dc.subject.fieldofresearch | Artificial intelligence | |
dc.subject.fieldofresearch | Applied mathematics | |
dc.subject.fieldofresearch | Automation engineering | |
dc.subject.fieldofresearch | Computer vision and multimedia computation | |
dc.subject.fieldofresearch | Machine learning | |
dc.subject.fieldofresearchcode | 4602 | |
dc.subject.fieldofresearchcode | 4901 | |
dc.subject.fieldofresearchcode | 400702 | |
dc.subject.fieldofresearchcode | 4603 | |
dc.subject.fieldofresearchcode | 4611 | |
dc.title | A Novel Cyber Attack Detection Method in Networked Control Systems | |
dc.type | Journal article | |
dc.type.description | C1 - Articles | |
dc.type.code | C - Journal Articles | |
dc.description.version | Accepted Manuscript (AM) | |
gro.faculty | Griffith Sciences, School of Engineering and Built Environment | |
gro.rights.copyright | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
gro.hasfulltext | Full Text | |
gro.griffith.author | Vlacic, Ljubo | |
gro.griffith.author | Yang, Fuwen | |