Tackling security and privacy challenges in the realm of big data analytics

Abstract

As organizations increasingly harness the power of big data analytics to derive insights and drive decision-making, the paramount concerns of security and privacy have come to the forefront. This paper presents a comprehensive framework for addressing the multifaceted challenges of big data security and privacy. Drawing on a synthesis of cutting-edge technologies, encryption methods, and access control mechanisms, our approach aims to fortify the entire big data lifecycle. The paper delves into innovative strategies for secure data storage, transmission, and processing, ensuring that sensitive information is shielded from unauthorized access or malicious attacks. Additionally, the framework incorporates robust privacy-preserving techniques, including anonymization and differential privacy, to uphold individual confidentiality. Through a meticulous analysis of current trends, emerging threats, and regulatory landscapes, this paper not only provides theoretical insights but also practical guidelines for organizations seeking to navigate the intricate landscape of big data while safeguarding the integrity, security, and privacy of the vast datasets at their disposal.