ReadMe Update for the Dataset

README.md

@@ -36,4 +36,60 @@ language:
 pretty_name: CyNER
 size_categories:
 - 1K<n<10K
----
+---
+# CyNER 2.0 Augmented Dataset
+*CyNER 2.0 Augmented Dataset* is a comprehensive dataset designed for Named Entity Recognition (NER) tasks, specifically tailored for cybersecurity-related text. This dataset combines an original cybersecurity NER dataset (bnsapa/cybersecurity-ner) with additional augmented data (taken from OPENCTI using AlienValut Connect), resulting in a robust resource for training and evaluating models on cybersecurity entity recognition.
+
+# Dataset Overview
+The dataset is divided into three splits:
+
+- Train: 7,751 examples
+- Validation: 1,661 examples
+- Test: 1,662 examples
+Each example in the dataset consists of a sequence of tokens and their corresponding NER tags.
+The dataset has been carefully preprocessed to ensure high quality and consistency.
+The dataset mostly contains threat and intelligence report descriptions from the Alien Vault
+
+# Features
+- tokens: A sequence of strings representing the tokens in the text.
+
+- ner_tags: A sequence of strings representing each token's Named Entity Recognition tags.
+
+# NER Tags
+The NER tags follow the BIO (Begin, Inside, Outside) tagging format and cover various cybersecurity-related entities, including but not limited to:
+
+- B-Indicator: Indicators of Compromise (IOCs) such as IP addresses, file hashes, and domain names.
+- I-Indicator: Continuation of an Indicator entity.
+- B-Malware: Names of malware, trojans, or viruses.
+- I-Malware: Continuation of a Malware entity.
+- B-Organization: Names of organisations, companies, or groups.
+- I-Organization: Continuation of an Organization entity.
+- B-System: Operating systems, software, and platforms.
+- I-System: Continuation of a System entity.
+- B-Vulnerability: Known vulnerabilities or CVEs (Common Vulnerabilities and Exposures).
+- I-Vulnerability: Continuation of a Vulnerability entity.
+- B-ThreatActor: Threat actor names or groups (e.g., Threat_group).
+- I-ThreatActor: Continuation of a ThreatActor entity.
+- B-Date: Specific dates related to incidents or reports.
+- I-Date: Continuation of a Date entity.
+- O: Outside of any named entity.
+# Usage
+This dataset is suitable for training, fine-tuning, and evaluating NER models, particularly those designed for cybersecurity applications. It has been structured to work seamlessly with popular NLP frameworks such as Hugging Face's transformers and dataset libraries.
+
+# License
+This dataset is released under the MIT License, which allows for open and flexible usage with minimal restrictions. Users are free to use, modify, and distribute the dataset, provided that proper attribution is given to the original creators.
+
+# Citation
+If you use this dataset in your research, please cite it as follows:
+```
+@dataset{pranava_kailash_2024_cyner,
+  title={CyNER 2.0 Augmented Dataset},
+  author={Pranava Kailash},
+  year={2024},
+  howpublished={Hugging Face, https://huggingface.co/datasets/PranavaKailash/CyNER2.0_augmented_dataset},
+  license={MIT}
+}
+```
+
+# Contact
+For questions or issues regarding the dataset, please get in touch with [email protected].