---
title: "Industrial control anomalies (SWaT, WADI): papers using it"
description: "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)."
url: https://scholar4ai.com/datasets/industrial-control-anomalies-swat-wadi
markdown_url: https://scholar4ai.com/datasets/industrial-control-anomalies-swat-wadi.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "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… (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# Industrial control anomalies (SWaT, WADI)

[Browse dataset profiles](https://scholar4ai.com/datasets/directory/page/4.md)

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

- data category: Cybersecurity and anomaly detection benchmarks
- 0 papers in the last 7 days
- Names searched for: WADI dataset, WADI testbed, Water Distribution testbed, SWaT, WADI

Most-used data: https://scholar4ai.com/rankings/datasets.md · All Cybersecurity and anomaly detection benchmarks datasets: https://scholar4ai.com/datasets/cybersecurity-and-anomaly-detection-benchmarks.md



## 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

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 8 | 5 | 5 |
| [Information Systems](https://scholar4ai.com/categories/information-systems.md) | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 3 | 0 | 3 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
| All categories | 0 | 0 | 0 | 0 | 1 | 0 | 7 | 12 | 5 | 8 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [Computers & Security](https://scholar4ai.com/journals/computers-security.md) | 7 |
| 2 | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 5 |
| 3 | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 3 |
| 4 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 3 |
| 5 | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 2 |
| 6 | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| 7 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 1 |
| 8 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 1 |
| 9 | [Computers & Industrial Engineering](https://scholar4ai.com/journals/computers-industrial-engineering.md) | 1 |
| 10 | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 1 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 5 |
| 2 | [Griffith University](https://scholar4ai.com/institutions/griffith-university.md) | 4 |
| 3 | [Monash University](https://scholar4ai.com/institutions/monash-university.md) | 4 |
| 4 | Edinburgh Napier University | 2 |
| 5 | [Harbin Institute of Technology](https://scholar4ai.com/institutions/harbin-institute-of-technology.md) | 2 |
| 6 | [Jinan University](https://scholar4ai.com/institutions/jinan-university.md) | 2 |
| 7 | La Trobe University | 2 |
| 8 | [Tianjin University](https://scholar4ai.com/institutions/tianjin-university.md) | 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](https://scholar4ai.com/keywords/anomaly-detection.md) | 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](https://scholar4ai.com/keywords/self-supervised-learning.md) | 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](https://doi.org/10.1109/tpami.2024.3387317) | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 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](https://doi.org/10.1016/j.knosys.2023.110941) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2023-09-01 | Riccardo Lazzarini, Huaglory Tianfield, Vassilis Charissis |
| 3 | 166 | 6.2 | [CARLA: Self-supervised contrastive representation learning for time series anomaly detection](https://doi.org/10.1016/j.patcog.2024.110874) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 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](https://doi.org/10.1016/j.knosys.2024.111849) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 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](https://doi.org/10.1109/tnnls.2023.3325667) | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 2023-11-14 | Yu Zheng, Huan Yee Koh, Ming Jin et al. |

## 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.

*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](https://scholar4ai.com/datasets/physionet-mit-bih.md) | Dataset | 4 | 26.0 |
| [Traffic (PeMS, METR-LA)](https://scholar4ai.com/datasets/traffic-pems-metr-la.md) | Dataset | 3 | 20.1 |
| [UCR / UEA archives](https://scholar4ai.com/datasets/ucr-uea-archives.md) | Dataset | 3 | 35.4 |

The whole network: https://scholar4ai.com/code/network.md

## 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

```bibtex
@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}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).