@inproceedings{c8d85bf76299468abe61ffb47219dcd8,
title = "Threat Miner - A Text Analysis Engine for Threat Identification Using Dark Web Data",
keywords = "Cyber Attacks, Cyber Threats, Dark web, Sentiment Analysis, Threat Intelligence",
author = "Nathan Deguara and Junaid Arshad and Anum Paracha and Azad, {Muhammad Ajmal}",
note = "Funding Information: The authors would like to pay gratitude to the Cambridge Cyber Crime Center, UK for the provision and accessibility to the CrimeBB dataset, which has been used to conduct this research. Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Big Data, Big Data 2022 ; Conference date: 17-12-2022 Through 20-12-2022",
year = "2023",
month = feb,
day = "26",
doi = "10.1109/BigData55660.2022.10020397",
language = "English",
series = "Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3043--3052",
editor = "Shusaku Tsumoto and Yukio Ohsawa and Lei Chen and {Van den Poel}, Dirk and Xiaohua Hu and Yoichi Motomura and Takuya Takagi and Lingfei Wu and Ying Xie and Akihiro Abe and Vijay Raghavan",
booktitle = "2022 IEEE International Conference on Big Data (Big Data)",
}