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Advances in Machine Learning for Explainable Intrusion Detection Using Imbalance Datasets in Cybersecurity with Harris Hawks Optimization

Year: 2025

Type: article

Abstract: Modern intrusion detection systems (MIDS) face persistent challenges in coping with the rapid evolution of cyber threats, high-volume network traffic, and imbalanced datasets. Traditional models often lack the robustness and ... | Find, read and cite all the research you need on Tech Science Press

Source: Computers, materials & continua/Computers, materials & continua (Print)

DOI: 10.32604/cmc.2025.068958

Authors: Amjad Rehman, Tanzila Saba, Mona M. Jamjoom, Shaha Al-Otaibi, Muhammad I. Khan

Institutions: Princess Nourah bint Abdulrahman University, Prince Sultan University

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: University of New South Wales, Princess Nourah Bint Abdulrahman University, Prince Sultan University

Award: G7891003125