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Abstract
As big data becomes an integral part of modern enterprises, ensuring the security and privacy of such data is both a technical and ethical imperative. The sheer volume, variety, and velocity of big data introduce complex challenges in securing data pipelines and safeguarding personal and sensitive information. This paper examines the primary security and privacy risks in big data environments, including access control, data anonymization, compliance, and vulnerability in distributed systems. It also proposes a framework for enhancing big data security and outlines emerging strategies like homomorphic encryption, differential privacy, and blockchain for secure data governance.
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