Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System

Wei Wang; Qiang Sun; Wenming Mei; Xiao Zhang; Xin Liu

doi:10.1109/ITAIC58329.2023.10409080

Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System

Wei Wang
, Qiang Sun
, Wenming Mei
, Xiao Zhang
, Xin Liu

State Grid Electric Power Research Institute Co., Ltd.
Shandong Electric Power Research Institute
State Grid Corporation of China

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

1 Scopus citations

Abstract

With the application of new technologies such as 'cloud computing, Big data, the Internet of Things, Artificial intelligence, 5G' in the power system and the development of smart grid, the multi stream integration of energy flow, business flow, and data flow, the interaction between the power internal network and the internet is becoming more frequently, and the boundaries of the power system network are constantly extending, shifting from closed to open, which will bring unprecedented network security risks and challenges. Traditional intrusion detection methods of information systems isn't suitable for power grid information physical system, and research on intrusion risk analysis for power grid information physical system is few currently. Therefore, according to the operation characteristics of the Power grid information physical system, this paper deeply analyzes the network intrusion risk of the power industrial control system, and summarizes the possible types of network attacks of the Power grid information physical system. Based on the risk types analyzed, this article proposes an intrusion detection method suitable for power grid information physical system, which also provides support for subsequent network tracing.

Original language	English
Title of host publication	IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference
Editors	Bing Xu, Kefen Mou
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	120-124
Number of pages	5
ISBN (Electronic)	9798350333664
DOIs	https://doi.org/10.1109/ITAIC58329.2023.10409080
State	Published - 2023
Externally published	Yes
Event	11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023 - Chongqing, China Duration: 8 Dec 2023 → 10 Dec 2023

Publication series

Name	IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
ISSN (Print)	2693-2865

Conference

Conference	11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023
Country/Territory	China
City	Chongqing
Period	8/12/23 → 10/12/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Attack detection
Network intrusion
Power grid information physical system
Power industry control protocol
Risk analysis

Access to Document

10.1109/ITAIC58329.2023.10409080

Cite this

Wang, W., Sun, Q., Mei, W., Zhang, X., & Liu, X. (2023). Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System. In B. Xu, & K. Mou (Eds.), IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (pp. 120-124). (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITAIC58329.2023.10409080

Wang, Wei ; Sun, Qiang ; Mei, Wenming et al. / Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System. IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference. editor / Bing Xu ; Kefen Mou. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 120-124 (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)).

@inproceedings{67944f12ea97448096ce12d33d8b944b,

title = "Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System",

abstract = "With the application of new technologies such as 'cloud computing, Big data, the Internet of Things, Artificial intelligence, 5G' in the power system and the development of smart grid, the multi stream integration of energy flow, business flow, and data flow, the interaction between the power internal network and the internet is becoming more frequently, and the boundaries of the power system network are constantly extending, shifting from closed to open, which will bring unprecedented network security risks and challenges. Traditional intrusion detection methods of information systems isn't suitable for power grid information physical system, and research on intrusion risk analysis for power grid information physical system is few currently. Therefore, according to the operation characteristics of the Power grid information physical system, this paper deeply analyzes the network intrusion risk of the power industrial control system, and summarizes the possible types of network attacks of the Power grid information physical system. Based on the risk types analyzed, this article proposes an intrusion detection method suitable for power grid information physical system, which also provides support for subsequent network tracing.",

keywords = "Attack detection, Network intrusion, Power grid information physical system, Power industry control protocol, Risk analysis",

author = "Wei Wang and Qiang Sun and Wenming Mei and Xiao Zhang and Xin Liu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023 ; Conference date: 08-12-2023 Through 10-12-2023",

year = "2023",

doi = "10.1109/ITAIC58329.2023.10409080",

language = "英语",

series = "IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "120--124",

editor = "Bing Xu and Kefen Mou",

booktitle = "IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference",

}

Wang, W, Sun, Q, Mei, W, Zhang, X & Liu, X 2023, Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System. in B Xu & K Mou (eds), IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference. IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Institute of Electrical and Electronics Engineers Inc., pp. 120-124, 11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023, Chongqing, China, 8/12/23. https://doi.org/10.1109/ITAIC58329.2023.10409080

Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System. / Wang, Wei; Sun, Qiang; Mei, Wenming et al.
IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference. ed. / Bing Xu; Kefen Mou. Institute of Electrical and Electronics Engineers Inc., 2023. p. 120-124 (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)).

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

TY - GEN

T1 - Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System

AU - Wang, Wei

AU - Sun, Qiang

AU - Mei, Wenming

AU - Zhang, Xiao

AU - Liu, Xin

PY - 2023

Y1 - 2023

N2 - With the application of new technologies such as 'cloud computing, Big data, the Internet of Things, Artificial intelligence, 5G' in the power system and the development of smart grid, the multi stream integration of energy flow, business flow, and data flow, the interaction between the power internal network and the internet is becoming more frequently, and the boundaries of the power system network are constantly extending, shifting from closed to open, which will bring unprecedented network security risks and challenges. Traditional intrusion detection methods of information systems isn't suitable for power grid information physical system, and research on intrusion risk analysis for power grid information physical system is few currently. Therefore, according to the operation characteristics of the Power grid information physical system, this paper deeply analyzes the network intrusion risk of the power industrial control system, and summarizes the possible types of network attacks of the Power grid information physical system. Based on the risk types analyzed, this article proposes an intrusion detection method suitable for power grid information physical system, which also provides support for subsequent network tracing.

AB - With the application of new technologies such as 'cloud computing, Big data, the Internet of Things, Artificial intelligence, 5G' in the power system and the development of smart grid, the multi stream integration of energy flow, business flow, and data flow, the interaction between the power internal network and the internet is becoming more frequently, and the boundaries of the power system network are constantly extending, shifting from closed to open, which will bring unprecedented network security risks and challenges. Traditional intrusion detection methods of information systems isn't suitable for power grid information physical system, and research on intrusion risk analysis for power grid information physical system is few currently. Therefore, according to the operation characteristics of the Power grid information physical system, this paper deeply analyzes the network intrusion risk of the power industrial control system, and summarizes the possible types of network attacks of the Power grid information physical system. Based on the risk types analyzed, this article proposes an intrusion detection method suitable for power grid information physical system, which also provides support for subsequent network tracing.

KW - Attack detection

KW - Network intrusion

KW - Power grid information physical system

KW - Power industry control protocol

KW - Risk analysis

UR - https://www.scopus.com/pages/publications/85186104507

U2 - 10.1109/ITAIC58329.2023.10409080

DO - 10.1109/ITAIC58329.2023.10409080

M3 - 会议稿件

AN - SCOPUS:85186104507

T3 - IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

SP - 120

EP - 124

BT - IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference

A2 - Xu, Bing

A2 - Mou, Kefen

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2023

Y2 - 8 December 2023 through 10 December 2023

ER -

Wang W, Sun Q, Mei W, Zhang X, Liu X. Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System. In Xu B, Mou K, editors, IEEE ITAIC 2023 - IEEE 11th Joint International Information Technology and Artificial Intelligence Conference. Institute of Electrical and Electronics Engineers Inc. 2023. p. 120-124. (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)). doi: 10.1109/ITAIC58329.2023.10409080

Research on Network Intrusion Risk and Behavior Detection Methods for Power Grid Information Physical System

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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