Inferring ICS Topology and Behavior through Network Traffic Analysis

Chien Wen Tseng; Jung Shian Li; Chu Fen Li; I-Hsien Liu

Inferring ICS Topology and Behavior through Network Traffic Analysis

Chien Wen Tseng
, Jung Shian Li
, Chu Fen Li
, I-Hsien Liu

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

Abstract

Ensuring the proper operation of industrial control systems (ICS) is a critical issue. Previous studies have focused on observing the controllers directly; however, this research proposes that analyzing network traffic could reduce system interference. This study utilizes a cybersecurity testing platform for dam systems to investigate network traffic to infer the composition of network nodes and the communication behavior between them. By doing so, it provides an alternative perspective for monitoring ICS operations. This model aids in understanding system topology, tracking potential deviations, and ensuring operational stability.

Original language	English
Title of host publication	Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025
Editors	Yingmin Jia, Takao Ito, Ju-Jang Lee
Publisher	ALife Robotics Corporation Ltd
Pages	128-131
Number of pages	4
ISBN (Print)	9784991333729
Publication status	Published - 2025
Event	30th International Conference on Artificial Life and Robotics, ICAROB 2025 - Oita, Japan Duration: 2025 Feb 13 → 2025 Feb 16

Publication series

Name	Proceedings of International Conference on Artificial Life and Robotics
ISSN (Electronic)	2435-9157

Conference

Conference	30th International Conference on Artificial Life and Robotics, ICAROB 2025
Country/Territory	Japan
City	Oita
Period	25-02-13 → 25-02-16

UN SDGs

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

SDG 9 Industry, Innovation, and Infrastructure

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Vision and Pattern Recognition
Hardware and Architecture
Information Systems
Control and Systems Engineering
Electrical and Electronic Engineering
Modelling and Simulation

Cite this

Tseng, C. W., Li, J. S., Li, C. F., & Liu, I.-H. (2025). Inferring ICS Topology and Behavior through Network Traffic Analysis. In Y. Jia, T. Ito, & J.-J. Lee (Eds.), Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025 (pp. 128-131). (Proceedings of International Conference on Artificial Life and Robotics). ALife Robotics Corporation Ltd.

Tseng, Chien Wen ; Li, Jung Shian ; Li, Chu Fen et al. / Inferring ICS Topology and Behavior through Network Traffic Analysis. Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025. editor / Yingmin Jia ; Takao Ito ; Ju-Jang Lee. ALife Robotics Corporation Ltd, 2025. pp. 128-131 (Proceedings of International Conference on Artificial Life and Robotics).

@inproceedings{a6f2c1ee4a234eeb9d9e0f1b4c01dbd6,

title = "Inferring ICS Topology and Behavior through Network Traffic Analysis",

abstract = "Ensuring the proper operation of industrial control systems (ICS) is a critical issue. Previous studies have focused on observing the controllers directly; however, this research proposes that analyzing network traffic could reduce system interference. This study utilizes a cybersecurity testing platform for dam systems to investigate network traffic to infer the composition of network nodes and the communication behavior between them. By doing so, it provides an alternative perspective for monitoring ICS operations. This model aids in understanding system topology, tracking potential deviations, and ensuring operational stability.",

author = "Tseng, \{Chien Wen\} and Li, \{Jung Shian\} and Li, \{Chu Fen\} and I-Hsien Liu",

note = "Publisher Copyright: {\textcopyright} The 2025 International Conference on Artificial Life and Robotics (ICAROB2025).; 30th International Conference on Artificial Life and Robotics, ICAROB 2025 ; Conference date: 13-02-2025 Through 16-02-2025",

year = "2025",

language = "English",

isbn = "9784991333729",

series = "Proceedings of International Conference on Artificial Life and Robotics",

publisher = "ALife Robotics Corporation Ltd",

pages = "128--131",

editor = "Yingmin Jia and Takao Ito and Ju-Jang Lee",

booktitle = "Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025",

}

Tseng, CW, Li, JS, Li, CF & Liu, I-H 2025, Inferring ICS Topology and Behavior through Network Traffic Analysis. in Y Jia, T Ito & J-J Lee (eds), Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025. Proceedings of International Conference on Artificial Life and Robotics, ALife Robotics Corporation Ltd, pp. 128-131, 30th International Conference on Artificial Life and Robotics, ICAROB 2025, Oita, Japan, 25-02-13.

Inferring ICS Topology and Behavior through Network Traffic Analysis. / Tseng, Chien Wen; Li, Jung Shian; Li, Chu Fen et al.
Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025. ed. / Yingmin Jia; Takao Ito; Ju-Jang Lee. ALife Robotics Corporation Ltd, 2025. p. 128-131 (Proceedings of International Conference on Artificial Life and Robotics).

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

TY - GEN

T1 - Inferring ICS Topology and Behavior through Network Traffic Analysis

AU - Tseng, Chien Wen

AU - Li, Jung Shian

AU - Li, Chu Fen

AU - Liu, I-Hsien

N1 - Publisher Copyright: © The 2025 International Conference on Artificial Life and Robotics (ICAROB2025).

PY - 2025

Y1 - 2025

N2 - Ensuring the proper operation of industrial control systems (ICS) is a critical issue. Previous studies have focused on observing the controllers directly; however, this research proposes that analyzing network traffic could reduce system interference. This study utilizes a cybersecurity testing platform for dam systems to investigate network traffic to infer the composition of network nodes and the communication behavior between them. By doing so, it provides an alternative perspective for monitoring ICS operations. This model aids in understanding system topology, tracking potential deviations, and ensuring operational stability.

AB - Ensuring the proper operation of industrial control systems (ICS) is a critical issue. Previous studies have focused on observing the controllers directly; however, this research proposes that analyzing network traffic could reduce system interference. This study utilizes a cybersecurity testing platform for dam systems to investigate network traffic to infer the composition of network nodes and the communication behavior between them. By doing so, it provides an alternative perspective for monitoring ICS operations. This model aids in understanding system topology, tracking potential deviations, and ensuring operational stability.

UR - https://www.scopus.com/pages/publications/85219536213

UR - https://www.scopus.com/pages/publications/85219536213#tab=citedBy

M3 - Conference contribution

AN - SCOPUS:85219536213

SN - 9784991333729

T3 - Proceedings of International Conference on Artificial Life and Robotics

SP - 128

EP - 131

BT - Proceedings of The 2025 International Conference on Artificial Life and Robotics, ICAROB 2025

A2 - Jia, Yingmin

A2 - Ito, Takao

A2 - Lee, Ju-Jang

PB - ALife Robotics Corporation Ltd

T2 - 30th International Conference on Artificial Life and Robotics, ICAROB 2025

Y2 - 13 February 2025 through 16 February 2025

ER -

Inferring ICS Topology and Behavior through Network Traffic Analysis

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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