PREDICTING PRIVACY RISKS IN BIG DATA ENVIRONMENTS: A MACHINE LEARNING APPROACH

• Dr. Ali Raza

  Department of Computer Science and Engineering, University of Peshawar, Pakistan.

In the modern age of big data, privacy risks have become a critical concern. The vast volume, velocity, and variety of data being generated every day increase the challenges of protecting personal and sensitive information. This article explores the potential of machine learning techniques in predicting privacy risks in big data environments. We introduce a comprehensive framework that integrates machine learning algorithms with data privacy mechanisms to enhance the prediction and mitigation of privacy vulnerabilities in data ecosystems. The study demonstrates how predictive models can be utilized to identify privacy threats, enabling organizations to take proactive measures to protect user information. By applying various machine learning models on large-scale datasets, the research highlights key patterns that could indicate potential privacy breaches, offering valuable insights for future data governance strategies.

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