Duplicate from dn-institute/cyberattack-blockchain-synth

Co-authored-by: Arina Razmyslovich <lavriz@users.noreply.huggingface.co>

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README.md

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+---
+language:
+- en
+license: unlicense
+size_categories:
+- 10K<n<100K
+task_categories:
+- text-classification
+- text-generation
+pretty_name: Cyberattack in Blockchain
+tags:
+- cyberattack
+- finance
+- blockchain
+- twitter
+- synthetic
+- llms
+---
+
+# ELTEX-Blockchain: A Domain-Specific Dataset for Cybersecurity
+🔐 **12k Synthetic Social Media Messages for Early Cyberattack Detection on Blockchain**
+
+## Dataset Statistics
+
+| **Category** | **Samples** | **Description** |
+|--------------|-------------|-----------------|
+| **Cyberattack** | 6,941 | Early warning signals and indicators of cyberattacks |
+| **General** | 4,507 | Regular blockchain discussions (non-security related) |
+
+## Dataset Structure
+
+Each entry in the dataset contains:
+- `message_id`: Unique identifier for each message
+- `content`: The text content of the social media message
+- `topic`: Classification label ("cyberattack" or "general")
+
+## Performance 
+[Gemma-2b-it](https://huggingface.co/google/gemma-2b-it) fine-tuned on this dataset:
+- Achieves a Brier score of 0.16 using only synthetic data in our social media threat detection task
+- Shows competitive performance on this specific task when compared to general-purpose models known for capabilities in cybersecurity tasks, like [granite-3.2-2b-instruct](https://huggingface.co/ibm-granite/granite-3.2-2b-instruct), and cybersecurity-focused LLMs trained on [Primus](https://huggingface.co/papers/2502.11191)
+- Demonstrates promising results for smaller models on this specific task, with our best hybrid model achieving an F1 score of 0.81 on our blockchain threat detection test set, though GPT-4o maintains superior overall accuracy (0.84) and calibration (Brier 0.10)
+
+## Attack Type Distribution
+
+| **Attack Vectors** | **Seed Examples** | 
+|-------------------|------------------------|
+| Social Engineering & Phishing | Credential theft, wallet phishing | 
+| Smart Contract Exploits | Token claim vulnerabilities, flash loans | 
+| Exchange Security Breaches | Hot wallet compromises, key theft |
+| DeFi Protocol Attacks | Liquidity pool manipulation, bridge exploits | 
+
+For more about Cyberattack Vectors, read [Attack Vectors Wiki](https://dn.institute/research/cyberattacks/wiki/)
+
+## Citation
+
+```bibtex
+@misc{razmyslovich2025eltexframeworkdomaindrivensynthetic,
+      title={ELTEX: A Framework for Domain-Driven Synthetic Data Generation}, 
+      author={Arina Razmyslovich and Kseniia Murasheva and Sofia Sedlova and Julien Capitaine and Eugene Dmitriev},
+      year={2025},
+      eprint={2503.15055},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2503.15055}, 
+}
+```