TTPDrill focuses on developing automated and context-aware analytics of cyber threat intelligence to accurately learn attack patterns (TTPs) from commonly available CTI sources in order to timely implement cyber defense actions. It implements data and text mining approach that combines enhanced techniques of Natural Language Processing (NLP) and Information Retrieval (IR) to extract threat actions based on semantic rather than syntactic relationships.
- Python 3
- stanford-corenlp jar, bert-base-srl tar, coref-model tar
- Clone this repository GitHub
- Add stanford-corenlp jar, bert-base-srl tar, coref-model tar
Copyright 2020 CyberDNA Center, UNC Charlotte
Please cite paper: https://dl.acm.org/doi/pdf/10.1145/3134600.3134646