Industrial control anomalies (SWaT, WADI)

data category: Cybersecurity and anomaly detection benchmarks · 0 papers in the last 7 days

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Network traffic, intrusion, fraud and anomaly records used to compare detection methods.

Names searched for: WADI dataset, WADI testbed, Water Distribution testbed, SWaT, WADI

Key findings#

From Nov 2023 to Oct 2026, 27 archived papers mentioned Industrial control anomalies (SWaT, WADI) in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Nov 2023 (2).
No paper of the tracked journals mentioned Industrial control anomalies (SWaT, WADI) in the last 30 days (2026-10-07 to 2026-11-05).
From 2017 to 2026 (so far), Industrial control anomalies (SWaT, WADI) was mentioned in 33 papers in the tracked journals, most of them in AI (23), information systems (9) and operations research (1).
5 of them were published in 2025, against 0 in 2017.
Since 2023, the institutions with the most of these papers were Zhejiang University (5), Griffith University (4) and Monash University (4).
The journals publishing most of them were Computers & Security (7), IEEE Transactions on Neural Networks and Learning Systems (5) and Applied Intelligence (3).
The most-cited of them is “Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024), with 295 citations.
Papers use Industrial control anomalies (SWaT, WADI) most often with PhysioNet / MIT-BIH (4), Traffic (PeMS, METR-LA) (3) and UCR / UEA archives (3); it has 3 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Trend	Nov 23–Oct 24	Nov 24–Oct 25	Nov 25–Oct 26	36 months
	10	8	9	27

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2021	2023	2024	2025	2026 (so far)
AI	0	5	8	5	5
Information Systems	1	2	3	0	3
Operations Research	0	0	1	0	0
All categories	1	7	12	5	8

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	Computers & Security	7
2	IEEE Transactions on Neural Networks and Learning Systems	5
3	Applied Intelligence	3
4	Knowledge-Based Systems	3
5	Pattern Recognition	2
6	Expert Systems with Applications	2
7	IEEE Transactions on Pattern Analysis and Machine Intelligence	1
8	Artificial Intelligence Review	1
9	Computers & Industrial Engineering	1
10	Neural Networks	1

Institutions with the most papers, since 2023
#	Institution	Papers
1	Zhejiang University	5
2	Griffith University	4
3	Monash University	4
4	Edinburgh Napier University	2
5	Harbin Institute of Technology	2
6	Jinan University	2
7	La Trobe University	2
8	Tianjin University	2
9	Xi’an University of Posts and Telecommunications	2
10	AGH University of Krakow	1

Countries with the most papers, since 2023
#	Country	Papers
1	China	17
2	United States	5
3	Australia	4
4	Germany	3
5	United Kingdom	2
6	Italy	2
7	Canada	1
8	Spain	1
9	France	1
10	Hong Kong	1

Keywords with the most papers, since 2023
#	Keyword	Papers
1	SWaT dataset	14
2	WADI dataset	13
3	anomaly detection	12
4	multivariate time series	10
5	industrial control systems	8
6	cyber-physical systems	5
7	intrusion detection	5
8	multivariate time series anomaly detection	5
9	time series anomaly detection	5
10	self-supervised learning	4

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	295	9.6	Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects	IEEE Transactions on Pattern Analysis and Machine Intelligence	2024-04-10	Kexin Zhang, Qingsong Wen, Chaoli Zhang et al.
2	199	5.2	A stacking ensemble of deep learning models for IoT intrusion detection	Knowledge-Based Systems	2023-09-01	Riccardo Lazzarini, Huaglory Tianfield, Vassilis Charissis
3	166	6.2	CARLA: Self-supervised contrastive representation learning for time series anomaly detection	Pattern Recognition	2024-08-09	Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan et al.
4	133	4.4	DTAAD: Dual Tcn-attention networks for anomaly detection in multivariate time series data	Knowledge-Based Systems	2024-04-23	Lingrui Yu, Qiuhong Lu, Yang Xue
5	113	3.2	Correlation-Aware Spatial–Temporal Graph Learning for Multivariate Time-Series Anomaly Detection	IEEE Transactions on Neural Networks and Learning Systems	2023-11-14	Yu Zheng, Huan Yee Koh, Ming Jin et al.

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use Industrial control anomalies (SWaT, WADI) most often with PhysioNet / MIT-BIH (4), Traffic (PeMS, METR-LA) (3) and UCR / UEA archives (3); it has 3 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →

What papers use Industrial control anomalies (SWaT, WADI) together with (at least 3 papers; lift 1 = chance)
Used with	Type	Papers using both	Lift
PhysioNet / MIT-BIH	Dataset	4	26.0
Traffic (PeMS, METR-LA)	Dataset	3	20.1
UCR / UEA archives	Dataset	3	35.4

Cite this page

Scholar4AI. (2026). Industrial control anomalies (SWaT, WADI). Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/industrial-control-anomalies-swat-wadi

@misc{scholar4ai-datasets-industrial-control-anomalies-swat-wadi,
  author = {{Scholar4AI}},
  title = {Industrial control anomalies (SWaT, WADI)},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/industrial-control-anomalies-swat-wadi}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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