PRIVACY AND SECURITY IN CLOUD-INTEGRATED BIG DATA SYSTEMS: A CASE STUDY APPROACH

Abstract

The integration of cloud computing and big data has revolutionized data storage, processing, and analytics. However, this convergence also presents significant challenges regarding data privacy, security breaches, and compliance with regulatory standards. This paper examines privacy and security concerns in cloud-integrated big data systems through a case study approach, identifying vulnerabilities, mitigation strategies, and best practices. By analyzing real-world implementations across healthcare, finance, and government sectors, this study provides actionable insights for designing more secure cloud-based big data infrastructures. Findings suggest that a combination of cryptographic techniques, decentralized architectures, and adaptive security models significantly enhances system resilience.