Dark Web Analytics: A Comparative Study of Feature Selection and Prediction Algorithms-Reference-Cited by-同舟云学术

Dark Web Analytics: A Comparative Study of Feature Selection and Prediction Algorithms

Published:2022-09-05 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Intelligent Data Science Technologies and Applications (IDSTA)
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Author:

Al-Omari Ahmad¹,Allhusen Andrew²,Wahbeh Abdullah³,Al-Ramahi Mohammad⁴,Alsmadi Izzat⁴

Affiliation:

1. Our Lady of the Lake University,CIS and Security Program,San Antonio,TX,USA

2. Syracuse University,Engineering & Computer Science,Syracuse,New York,USA

3. Slippery Rock University,Dept. of computer science,Slippery Rock,Pennsylvania

4. Texas A&M, San Antonio,Dept. of computing and cyber security,San Antonio,Texas

Publisher

IEEE

Link

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1. Illuminating the Dark: Gaining Insights and Managing Risks with Dark Analytics;2024 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE);2024-01-24

2. Enhancing Darknet Traffic Analysis through Top Ranked Feature Selection Methods;2023 International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS);2023-09-15