A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System

Baoyue Xu; Dajun Du; Changda Zhang; Jin Zhang

doi:10.23919/CCC52363.2021.9550229

A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System

Baoyue Xu, Dajun Du, Changda Zhang, Jin Zhang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The data transmitted via the network may be vulnerable to cyber attacks in networked inverted pendulum system (NIPS), how to detect cyber attacks is a challenging issue. To solve this problem, this paper investigates a honeypot-based attack detection method for NIPS. Firstly, honeypot for NIPS attack detection (namely NipsPot) is constructed by deceptive environment module of a virtual closed-loop control system, and the stealthiness of typical covert attacks is analysed. Secondly, attack data is collected by NipsPot, which is used to train supported vector machine (SVM) model for attack detection. Finally, simulation results demonstrate that NipsPot-based attack detector can achieve the accuracy rate of 99.78%, the precision rate of 98.75%, and the recall rate of 100%.

Original language	English
Title of host publication	Proceedings of the 40th Chinese Control Conference, CCC 2021
Editors	Chen Peng, Jian Sun
Publisher	IEEE Computer Society
Pages	8645-8650
Number of pages	6
ISBN (Electronic)	9789881563804
DOIs	https://doi.org/10.23919/CCC52363.2021.9550229
State	Published - 26 Jul 2021
Externally published	Yes
Event	40th Chinese Control Conference, CCC 2021 - Shanghai, China Duration: 26 Jul 2021 → 28 Jul 2021

Publication series

Name	Chinese Control Conference, CCC
Volume	2021-July
ISSN (Print)	1934-1768
ISSN (Electronic)	2161-2927

Conference

Conference	40th Chinese Control Conference, CCC 2021
Country/Territory	China
City	Shanghai
Period	26/07/21 → 28/07/21

Keywords

NipsPot
covert attacks
networked inverted pendulum system
supported vector machine

Access to Document

10.23919/CCC52363.2021.9550229

Cite this

@inproceedings{1a22ed9e9d8544aa9da2929ea13d9896,

title = "A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System",

abstract = "The data transmitted via the network may be vulnerable to cyber attacks in networked inverted pendulum system (NIPS), how to detect cyber attacks is a challenging issue. To solve this problem, this paper investigates a honeypot-based attack detection method for NIPS. Firstly, honeypot for NIPS attack detection (namely NipsPot) is constructed by deceptive environment module of a virtual closed-loop control system, and the stealthiness of typical covert attacks is analysed. Secondly, attack data is collected by NipsPot, which is used to train supported vector machine (SVM) model for attack detection. Finally, simulation results demonstrate that NipsPot-based attack detector can achieve the accuracy rate of 99.78%, the precision rate of 98.75%, and the recall rate of 100%.",

keywords = "NipsPot, covert attacks, networked inverted pendulum system, supported vector machine",

author = "Baoyue Xu and Dajun Du and Changda Zhang and Jin Zhang",

note = "Publisher Copyright: {\textcopyright} 2021 Technical Committee on Control Theory, Chinese Association of Automation.; 40th Chinese Control Conference, CCC 2021 ; Conference date: 26-07-2021 Through 28-07-2021",

year = "2021",

month = jul,

day = "26",

doi = "10.23919/CCC52363.2021.9550229",

language = "אנגלית",

series = "Chinese Control Conference, CCC",

publisher = "IEEE Computer Society",

pages = "8645--8650",

editor = "Chen Peng and Jian Sun",

booktitle = "Proceedings of the 40th Chinese Control Conference, CCC 2021",

address = "ארצות הברית",

}

Xu, B, Du, D, Zhang, C & Zhang, J 2021, A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System. in C Peng & J Sun (eds), Proceedings of the 40th Chinese Control Conference, CCC 2021. Chinese Control Conference, CCC, vol. 2021-July, IEEE Computer Society, pp. 8645-8650, 40th Chinese Control Conference, CCC 2021, Shanghai, China, 26/07/21. https://doi.org/10.23919/CCC52363.2021.9550229

A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System. / Xu, Baoyue; Du, Dajun; Zhang, Changda et al.
Proceedings of the 40th Chinese Control Conference, CCC 2021. ed. / Chen Peng; Jian Sun. IEEE Computer Society, 2021. p. 8645-8650 (Chinese Control Conference, CCC; Vol. 2021-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System

AU - Xu, Baoyue

AU - Du, Dajun

AU - Zhang, Changda

AU - Zhang, Jin

PY - 2021/7/26

Y1 - 2021/7/26

N2 - The data transmitted via the network may be vulnerable to cyber attacks in networked inverted pendulum system (NIPS), how to detect cyber attacks is a challenging issue. To solve this problem, this paper investigates a honeypot-based attack detection method for NIPS. Firstly, honeypot for NIPS attack detection (namely NipsPot) is constructed by deceptive environment module of a virtual closed-loop control system, and the stealthiness of typical covert attacks is analysed. Secondly, attack data is collected by NipsPot, which is used to train supported vector machine (SVM) model for attack detection. Finally, simulation results demonstrate that NipsPot-based attack detector can achieve the accuracy rate of 99.78%, the precision rate of 98.75%, and the recall rate of 100%.

AB - The data transmitted via the network may be vulnerable to cyber attacks in networked inverted pendulum system (NIPS), how to detect cyber attacks is a challenging issue. To solve this problem, this paper investigates a honeypot-based attack detection method for NIPS. Firstly, honeypot for NIPS attack detection (namely NipsPot) is constructed by deceptive environment module of a virtual closed-loop control system, and the stealthiness of typical covert attacks is analysed. Secondly, attack data is collected by NipsPot, which is used to train supported vector machine (SVM) model for attack detection. Finally, simulation results demonstrate that NipsPot-based attack detector can achieve the accuracy rate of 99.78%, the precision rate of 98.75%, and the recall rate of 100%.

KW - NipsPot

KW - covert attacks

KW - networked inverted pendulum system

KW - supported vector machine

UR - http://www.scopus.com/inward/record.url?scp=85117321123&partnerID=8YFLogxK

U2 - 10.23919/CCC52363.2021.9550229

DO - 10.23919/CCC52363.2021.9550229

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85117321123

T3 - Chinese Control Conference, CCC

SP - 8645

EP - 8650

BT - Proceedings of the 40th Chinese Control Conference, CCC 2021

A2 - Peng, Chen

A2 - Sun, Jian

PB - IEEE Computer Society

T2 - 40th Chinese Control Conference, CCC 2021

Y2 - 26 July 2021 through 28 July 2021

ER -

A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this