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Enhancing Cloud Security with Machine Learning by Neliswa Mkhwanazi is a document available to read on EtoBox.

The study focuses on improving cybersecurity at Durban University of Technology through the application of machine learning models in a hybrid cloud environment. Three models were evaluated: Convolutional Neural Networks achieved 99% accuracy, Support Vector Machines 96% in binary classification, and K-means clustering was useful for anomaly detection despite lower accuracy. Future work suggests using real-time data for validation, optimizing models for real-time applications, and exploring collaborative se

Author

Neliswa Mkhwanazi

Language

EN