---
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- mitre_ttps
- security
- adversarial-threat-annotation
---

# SentSecBert

This is a [sentence-transformers](https://www.SBERT.net) model: It maps sentences & paragraphs to a 768 dimensional dense vector space and can be used for tasks like clustering or semantic search.

This is a model used in our work "Semantic Ranking for Automated Adversarial Technique Annotation in Security Text". The code is available at: [https://github.com/qcri/Text2TTP](https://github.com/qcri/Text2TTP)

## Usage (Sentence-Transformers)

Using this model becomes easy when you have [sentence-transformers](https://www.SBERT.net) installed:

```
pip install -U sentence-transformers
```

Then you can use the model like this:

```python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]

model = SentenceTransformer('SentSecBert')
embeddings = model.encode(sentences)
print(embeddings)
```

## Citation
```
@article{kumarasinghe2024semantic,
  title={Semantic Ranking for Automated Adversarial Technique Annotation in Security Text},
  author={Kumarasinghe, Udesh and Lekssays, Ahmed and Sencar, Husrev Taha and Boughorbel, Sabri and Elvitigala, Charitha and Nakov, Preslav},
  journal={arXiv preprint arXiv:2403.17068},
  year={2024}
}
```