Update README.md

README.md

@@ -7,4 +7,65 @@ language:
 tags:
 - cyber
 pretty_name: Anno CTR
----
+---
+
+<!---
+
+    Copyright (c) 2023 Robert Bosch GmbH and its subsidiaries.
+
+-->
+
+# AnnoCTR Resources
+
+This repository contains the companion material for the following publication:
+
+> Lukas Lange, Marc Müller, Ghazaleh Haratinezhad Torbati, Dragan Milchevski, Patrick Grau, Subhash Pujari, Annemarie Friedrich. **AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports.** LREC-COLING 2024.
+
+Please cite this paper if using the dataset or the code, and direct any questions to [Lukas Lange](mailto:lukas.lange@de.bosch.com).
+The paper can be found at the [ACL Anthology (tbd.)](https://www.aclweb.org/anthology/TODO/) or at
+[ArXiv](https://arxiv.org/abs/2404.07765).
+
+
+## Purpose of this Software 
+
+This software is a research prototype, solely developed for and published as
+part of the publication cited above. It will neither be maintained nor monitored in any way.
+
+
+## The AnnoCTR Corpus
+
+AnnoCTR consists of 400 cyber threat reports that have been obtained from commercial CTI vendors. 
+The reports describe threat-related information such as tactics, techniques, actors, tools, and targeted industries. 
+The reports have been annotated by a domain expert with named entities, temporal expressions, and cybersecurity-specific concepts. 
+The annotations include mentions of organizations, locations, industry sectors, time expressions, 
+code snippets, hacker groups, malware, tools, tactics, and techniques.
+
+The dataset is split into three parts: train, dev, and test, with 60%, 15%, and 25% of the documents, 
+respectively. 
+The train set is used for model training, the dev set is used for model selection, 
+and the test set is used for evaluation.
+
+For further information on the annotation scheme, 
+please refer to our paper and the annotation guidelines for the 
+[general concepts](Annotation_Guidelines_General_Layer.pdf) and 
+[cybersecurity-specific concepts](Annotation_Guidelines_Cysec_Layer.pdf).
+
+### Corpus File Formats
+
+This is an HF friendly dataset loader for training LLMs on the NER tags.
+
+
+### Acknowledgements
+
+The reports have been kindly donated by 
+[Intel471](https://intel471.com/blog}), 
+[Lab52](https://lab52.io/blog/), 
+the [threat intelligence division of S2 Grupo](https://s2grupo.es/), 
+[Proofpoint](https://www.proofpoint.com/us/blog), 
+[QuoIntelligence](https://quointelligence.eu/blog), 
+and [ZScaler](https://www.zscaler.com/blogs/security-research).
+
+
+## License
+
+The AnnoCTR corpus located in the folder [AnnoCTR](AnnoCTR) is licensed under a [Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/) (CC-BY-SA 4.0).