---
title: "microsoft/CyberBattleSim: papers citing it"
description: "6 papers in the tracked journals link to the GitHub repository microsoft/CyberBattleSim in their Crossref records, the first in 2025; most of them (3) in 2026."
url: https://scholar4ai.com/code/github-microsoft-cyberbattlesim
markdown_url: https://scholar4ai.com/code/github-microsoft-cyberbattlesim.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "6 papers in the tracked journals link to the GitHub repository microsoft/CyberBattleSim in their Crossref records, the first in 2025; most of them (3) in 2026. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# microsoft/CyberBattleSim: papers linking to it

Research papers in the 480 tracked journals that link to microsoft/CyberBattleSim (https://github.com/microsoft/CyberBattleSim), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 1,805 stars
- 283 forks
- Jupyter Notebook
- license MIT
- created 2020
- https://github.com/microsoft/CyberBattleSim

All repositories: https://scholar4ai.com/code.md

## Key findings

- 6 papers in the tracked journals link to the GitHub repository microsoft/CyberBattleSim in their Crossref records, the first in 2025; most of them (3) in 2026.
- By category: AI (5) and Operations Research (1); the journals with the most are Expert Systems with Applications (3), Annals of Operations Research (1) and Applied Intelligence (1).

## By year

*Papers linking to microsoft/CyberBattleSim by publication year*

| Year | Papers |
|---|---:|
| 2025 | 3 |
| 2026 | 3 |

## Journals

*Journals whose papers link to microsoft/CyberBattleSim most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 3 |
| [Annals of Operations Research](https://scholar4ai.com/journals/annals-of-operations-research.md) | 1 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Artificial Intelligence](https://scholar4ai.com/journals/artificial-intelligence.md) | 1 |

## Papers

*Papers linking to microsoft/CyberBattleSim, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2025-07-26 | [Reinforcement Learning in action: Powering intelligent intrusion responses to advanced cyber threats in realistic scenarios](https://doi.org/10.1016/j.eswa.2025.129168) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Eider Iturbe, Angel Rego, Oscar Llorente-Vazquez et al. | 8 | cites it |
| 2025-11-11 | [Autonomous penetration testing using reinforcement learning: A review and perspectives](https://doi.org/10.1016/j.eswa.2025.130219) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Jingju Liu, Yue Zhang, Shicheng Zhou et al. | 6 | cites it |
| 2025-10-15 | [Building adaptative and transparent cyber agents with local language models](https://doi.org/10.1016/j.eswa.2025.129987) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | María Rigaki, Carlos Adrian Catania, Sebastián García | 2 | cites it |
| 2026-08-25 | [Reinforcement Learning for decision support in defense and security: A systematic review](https://doi.org/10.1007/s10479-026-07205-x) | [Annals of Operations Research](https://scholar4ai.com/journals/annals-of-operations-research.md) | Maarten P. D. Schadd, David S. Berman, C.M. Chen et al. | 2 | cites it |
| 2026-04-11 | [Decision-theoretic planning and cognitive modeling for active cyber deception](https://doi.org/10.1016/j.artint.2026.104540) | [Artificial Intelligence](https://scholar4ai.com/journals/artificial-intelligence.md) | Aditya Shinde, Prashant Doshi | 0 | cites it |
| 2026-07-01 | [A systematic evaluation of large language models for autonomous cyber defense](https://doi.org/10.1007/s10489-026-07386-9) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Thibaut Jacques | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). microsoft/CyberBattleSim: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-microsoft-cyberbattlesim

```bibtex
@misc{scholar4ai-code-github-microsoft-cyberbattlesim,
  author = {{Scholar4AI}},
  title = {microsoft/CyberBattleSim: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-microsoft-cyberbattlesim}},
  urldate = {2026-11-03},
  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/).