Enhancing Cloud Security in Indian Enterprises: A Machine Learning Approach
DOI:
https://doi.org/10.36676/urr.v8.i4.1408Keywords:
Cloud Security, Machine Learning, Anomaly DetectionAbstract
Cloud adoption in Indian enterprises is on the rise, bringing with it significant security challenges. This paper investigates how machine learning techniques can be applied to bolster cloud security in Indian organizations. The research focuses on anomaly detection systems that use machine learning algorithms to identify suspicious activities in cloud environments. Models such as Random Forest, Gradient Boosting, and Neural Networks are evaluated based on their ability to detect threats such as Distributed Denial of Service (DDoS) attacks, insider threats, and data breaches. The paper also discusses the need for localized cloud security frameworks tailored to Indian regulatory requirements and data privacy laws.
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