MUT INSTITUTIONAL RESEARCH ARCHIVE
An Institutional Repository (IR) is a digital service that collects, preserves, and distributes digital material. It serves as the home for the intellectual output of MUT academic communities, and will ultimately include digital dissertations, faculty publications, digital special collections, open access publications, open educational resources and much more.
Communities in Research Archive
Select a community to browse its collections.
Recently Added
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Discriminative spatial-temporal feature learning for modeling network intrusion detection systems
(Journal of Computer Security, 2023-02)Increasing interest and advancement of internet and communication technologies have made network security rise as a vibrant research domain. Network intrusion detection systems (NIDSs) have developed as indispensable defense ... -
A Suite of Metrics for UML Behavioral Diagrams Based on Complexity Perspectives
(International Journal of Software Engineering & Applications, 2024-03)Nowadays, software designers have adopted modelling languages that help to communicate the dynamic behavior of UML behavioral diagrams. As it is with other software artefacts, these diagrams tend to get more complex ... -
A Novel Alert Correlation Technique for Filtering Network Attacks
(International Journal of Network Security & Its Applications, 2023-05)An alert correlation is a high-level alert evaluation technique for managing large volumes of irrelevant and redundant intrusion alerts raised by Intrusion Detection Systems (IDSs).Recent trends show that pure intrusion ... -
Multi-Agent Systems Requirements Analysis for Patient-centered Healthcare Consultancy Service
(International Journal of Advanced Research in Computer Science, 2023-10)Agents are currently being discussed in nearly every domain of science and engineering. Through the utilization of IoT and agent-based systems, remote consultations and virtual doctors can provide essential healthcare ... -
Application of Real-Time Deep Learning in integrated Surveillance of Maize and Tomato Pests and Bacterial Diseases
(Journal of the Kenya National Commission for UNESCO, 2024-01)With an emphasis on maize and tomato crops specifically, this research explores the creative fusion of computer vision (CV) and machine learning (ML) to address the enduring problem of pests and crop diseases impacting ...