Navigating Security Risks in Large-Scale Data Handling: A Big Data and Mis Perspective

Abstract

The exponential rise of big data has revolutionized sectors like healthcare, finance, and e-commerce while introducing complex security challenges. As organizations increasingly rely on vast datasets for decision-making and innovation, they face heightened risks of data breaches, unauthorized access, and cyberattacks. This study, conducted at the Department of Management Information Systems, Lamar University, Beaumont, TX, USA, from January 2022 to December 2023, investigates these security risks from a Management Information Systems (MIS) perspective, aiming to identify key vulnerabilities and propose effective mitigation strategies. Utilizing a mixed-method approach, the research integrates qualitative interviews with 50 IT professionals and quantitative data from 10 organizations managing large-scale datasets. Data analysis was performed using SPSS version 26, focusing on encryption, role-based access control (RBAC), and real-time anomaly detection. The results revealed that the healthcare sector experienced the highest breach rate at 60%, while e-commerce followed closely at 50%. Encryption proved highly effective, reducing breaches by 45%, and real-time anomaly detection systems reduced breaches by 50%. RBAC minimized insider threats, contributing to a 35% reduction in breaches. Furthermore, adopting data governance frameworks improved regulatory compliance by 45%, with 85% of organizations implementing advanced encryption techniques. This study highlights the necessity of integrating sophisticated security measures, such as encryption, RBAC, and anomaly detection, within MIS frameworks to safeguard sensitive data. A multi-layered security approach is crucial for ensuring data protection and regulatory compliance in today's data-driven landscape.