From Feature Engineering and Topics Models to Enhanced Prediction Rates in Phishing Detection

Author:

Gualberto Eder S.ORCID,De Sousa Rafael T.ORCID,De B. Vieira Thiago P.ORCID,Da Costa Joao Paulo C. L.ORCID,Duque Claudio G.ORCID

Funder

CNPq - Brazilian National Research Council

CAPES - Brazilian Higher Education Personnel Improvement Coordination

FAP-DF - Brazilian Federal District Research Support Foundation

Brazilian Ministry of the Economy

Institutional Security Office of the Presidency of Brazil

Administrative Council for Economic Defense

General Attorney of the Union

DPI/DPG/UnB–Decanates of Research and Innovation and Postgraduate Studies of the University of Brasilia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

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3. Multi-Class Text Classification Based in Oversampling for Highly Imbalanced Dataset;2023 International Conference on Machine Learning and Applications (ICMLA);2023-12-15

4. Machine Learning-Based Phishing E-mail Detection Using Persuasion Principle and NLP Techniques;Proceedings of International Conference on Network Security and Blockchain Technology;2023-11-29

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