---
title: "microsoft/SEAL: papers citing this GitHub repository"
description: "5 papers in the tracked journals link to the GitHub repository microsoft/SEAL in their Crossref records, the first in 2021; most of them (2) in 2026."
url: https://scholar4ai.com/code/github-microsoft-seal
markdown_url: https://scholar4ai.com/code/github-microsoft-seal.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "5 papers in the tracked journals link to the GitHub repository microsoft/SEAL in their Crossref records, the first in 2021; most of them (2) 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/SEAL: papers linking to it

Research papers in the 480 tracked journals that link to microsoft/SEAL (https://github.com/microsoft/SEAL), 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
- 4,065 stars
- 779 forks
- C++
- license MIT
- created 2018
- https://github.com/microsoft/SEAL

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

## Key findings

- 5 papers in the tracked journals link to the GitHub repository microsoft/SEAL in their Crossref records, the first in 2021; most of them (2) in 2026.
- By category: AI (5); the journals with the most are Expert Systems with Applications (2), Applied Intelligence (1) and Neural Computing and Applications (1).
- 2 of the papers build on one another: a later paper cites an earlier one that also links microsoft/SEAL.

## By year

*Papers linking to microsoft/SEAL by publication year*

| Year | Papers |
|---|---:|
| 2021 | 1 |
| 2024 | 1 |
| 2025 | 1 |
| 2026 | 2 |

## Journals

*Journals whose papers link to microsoft/SEAL most*

| Journal | Papers |
|---|---:|
| [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 |
| [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |
| [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | 1 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Support vector machine classification over encrypted data](https://doi.org/10.1007/s10489-021-02727-2) (Applied Intelligence, 2021)
  - [EVAD: encrypted vibrational anomaly detection with homomorphic encryption](https://doi.org/10.1007/s00521-024-09464-w) (Neural Computing and Applications, 2024) — cites the paper above

## Papers

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

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2021-08-25 | [Support vector machine classification over encrypted data](https://doi.org/10.1007/s10489-021-02727-2) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | Hai Huang, Yongjian Wang, Haoran Zong | 26 | cites it |
| 2024-03-01 | [EVAD: encrypted vibrational anomaly detection with homomorphic encryption](https://doi.org/10.1007/s00521-024-09464-w) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Alessandro Falcetta, Manuel Roveri | 11 | cites it |
| 2025-11-17 | [Preserving data and model privacy during inference and training](https://doi.org/10.1016/j.eswa.2025.130167) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | William Briguglio, Issa Traoré, Mohammad Mamun et al. | 0 | cites it |
| 2026-09-01 | [Privacy-preserving methodologies against privacy attacks on deep learning: a survey](https://doi.org/10.1007/s10115-026-02865-4) | [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | Subhasish Ghosh, Amit Kr Mandal | 0 | cites it |
| 2026-10-01 | [ARION: Attention-Optimized Transformer Inference on Encrypted Data](https://doi.org/10.1016/j.eswa.2026.134756) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Linhan Yang, Jingwei Chen, Wangchen Dai et al. | 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/SEAL: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-microsoft-seal

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