Enhancing Big Data Security through Comprehensive Data Protection Measures: A Focus on Securing Data at Rest and In-Transit

Abstract

Purpose: This research paper aims to enhance Big Data security by implementing comprehensive data protection measures, focusing on securing data at rest and in transit. In the era of Big Data, organizations handle vast quantities of data characterized by high velocity, volume, and variety, which complicates management and increases security risks. Methodology: The study examines various data protection strategies, including encryption, access control, data masking, immutable storage, tokenization, and physical security for data at rest. For data in transit, it explores encryption protocols, secure transfer methods like SSH and TLS, VPNs, Zero Trust architecture, and secure APIs. These methods are crucial for safeguarding sensitive information and preventing unauthorized access. Findings: The findings highlight common security challenges in Big Data, such as data breaches, unauthorized access, and integrity issues. The study emphasizes the need for robust protection measures and offers a comprehensive view of the data security landscape. Implementing these strategies helps organizations safeguard sensitive information and ensure compliance with international data protection regulations, enhancing their overall security posture. Unique contribution to theory policy and practice: This paper contributes to theory, policy, and practice by advocating comprehensive data protection strategies. It stresses the importance of continuous monitoring and regulatory compliance, providing practical insights into best practices and technologies that protect Big Data. The research supports developing robust data protection policies and practices, advancing knowledge in Big Data security.