Advancements and Best Practices in Data Loss Prevention: A Comprehensive Review

Abstract

DLP solutions are needed because there is more data and more reliance on it which people and businesses need. This paper will provide a further account of what DLP is, its significance, issues it encounters, and prospects in what follows from this article about DLP. Globalization and the rise in the kind and level of cyber threats, uptick in cloud use, and the enhancement of legal requirements for data protection have all moved DLP to higher prominence as a cybersecurity mechanism. In more detail, some challenges that are associated with DLP implementation and that refers to initiation and management, are described, such as data classification, security needs and organization productivity, insiders and their threats, regulation compliance, and others. The article also examines how data protection paradigms are revolutionized by AI, ML, cloud native DLP solutions, Zero Trust architecture, and XDR. Also, it underlines the need of privacy by design, and the controls concerning insider threats in the shift of the paradigm. As the type and functionality of DLP systems will further advance not in the distant future, utilization of such state of the art technologies shall assist organizations to secure data while the latter focus on continued operation. Therefore to meet this ever present need for such smart and dynamic DLP solutions to address data loss consideration in the multiple complex cloud environment there is need to rise new and complex cyber threats.