Investigating Machine Learning Algorithms for Enhancing Data Security in Cloud Computing Environments

1. Introduction 1.1 Background and Motivation 1.2 Objectives of the Study 1.3 Research Questions 1.4 Structure of the Thesis 2. Literature Review 2.1 Overview of Cloud Computing 2.2 Data Security Challenges 2.3 Machine Learning in Cybersecurity 2.4 Related Work 3. Machine Learning Algorithms 3.1 Supervised Learning Techniques 3.2 Unsupervised Learning Methods 3.3 Reinforcement Learning Applications 3.4 Deep Learning Approaches 4. Data Security in Cloud 4.1 Encryption Techniques 4.2 Access Control Mechanisms 4.3 Intrusion Detection Systems 4.4 Privacy Preservation 5. Enhancing Security with Machine Learning 5.1 Threat Detection Models 5.2 Anomaly Detection Algorithms 5.3 User Authentication Solutions 6. Case Studies and Applications 6.1 Case Study: Amazon Web Services 6.2 Case Study: Google Cloud Platform 6.3 Case Study: Microsoft Azure 7. Evaluation and Result Analysis 7.1 Performance Metrics 7.2 Comparative Analysis 7.3 Discussion of Results 8. Conclusion and Future Work 8.1 Summary of Findings 8.2 Limitations of the Study 8.3 Recommendations for Future Research