Zeus banking malware; Zeus malware variants; machine learning; binary classification algorithms; deep learning; feature selection

Kazi, Mohamed ORCID: https://orcid.org/0000-0001-5105-3581, Woodhead, Steve and Gan, Diane ORCID: https://orcid.org/0000-0002-0920-7572 (2022) An investigation to detect banking malware network communication traffic using machine learning techniques. Journal of Cybersecurity and Privacy, 3 (1). pp. 1-23. ISSN 2624-800X (Online) (doi:10.3390/jcp3010001)

Zeus banking malware; detecting banking malware using binary classification algorithms; decision tree algorithm; random forest algorithm; SVM algorithm; manual feature selection

Kazi, Mohamed ORCID: https://orcid.org/0000-0001-5105-3581, Woodhead, Steve and Gan, Diane ORCID: https://orcid.org/0000-0002-0920-7572 (2020) Comparing and analysing binary classification algorithms when used to detect the Zeus malware. In: 2019 Sixth HCT Information Technology Trends (ITT). Ras Al Khaimah, United Arab Emirates, 20-21 Nov. 2019. Information Technology Trends (ITT) . Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, pp. 6-11. ISBN 978-1728150611; 978-1728150628 (doi:10.1109/ITT48889.2019.9075115)