Data Privacy and Security Challenges in Big Data Analytics: A Review of Current Solutions and Future Directions

Abstract

The growing amount of data generated by our daily activities, known as big data, presents distinctive challenges due to its scale, complexity, and velocity. Big data analytics is the process of collecting and analyzing this data to uncover insights and gain a competitive advantage. However, as the use of big data continues to increase, the importance of data privacy and security has become more critical. The sheer size and complexity of big data sets can make it difficult to implement privacy and security algorithms that work at the necessary scale and speed. Therefore, there is a need to explore current solutions and future directions for addressing the data privacy and security challenges in big data analytics. This review aims to provide an overview of the current state of knowledge in this field, including a discussion of the challenges and potential solutions for ensuring data privacy and security in the context of big data analytics. By identifying the gaps in the literature and proposing future research directions, this review intends to contribute to a deeper understanding of the data privacy and security challenges in big data analytics and inform the development of more effective solutions.