AN IMPROVED MACHINE LEARNING CLASSIFICATION-BASED ALGORITHM FOR DETECTION OF DATA LEAKAGES IN A CLOUD COMPUTING ENVIRONMENT: A REVIEW

Computer Science

Cloud computing has introduced new security challenges, particularly in preventing data leakages. To address this issue, we propose an improved machine learning classification-based algorithm for detecting data leakages in cloud computing environments. Our algorithm leverages machine learning techniques to identify anomalous patterns and behaviors that may indicate potential leakages. We utilize a comprehensive feature selection process and consider factors such as file access patterns, user behavior, and network traffic to enhance detection capabilities. Large dataset was used to train the algorithm and high-tech machine learning algorithms was employed. Experimental results exhibit higher performance compare to conventional methods in terms of accuracy and efficiency. The real-time detection capabilities of the algorithm enable organizations to prevent and mitigate data breaches, safeguarding their sensitive information. Future research can focus on refining and integrating the algorithm into existing cloud security frameworks for enhanced data protection.

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