| Title | A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Xu, Baoyue, Du, Dajun, Zhang, Changda, Zhang, Jin |
| Conference Name | 2021 40th Chinese Control Conference (CCC) |
| Keywords | attack vectors, control systems, covert attacks, cyberattack, Data models, Detectors, Human Behavior, networked inverted pendulum system, NipsPot, pubcrawl, Resiliency, Scalability, simulation, Support vector machines, supported vector machine, Training |
| 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%. |
| DOI | 10.23919/CCC52363.2021.9550229 |
| Citation Key | xu_honeypot-based_2021 |
A Honeypot-based Attack Detection Method for Networked Inverted Pendulum System