In this presentation, we will start by exploring the history of Data Loss Prevention (DLP) and why it was such a significant challenge in the past. We will explain what has changed and then define DLP, outlining its main purpose and highlighting the essential role it plays in protecting sensitive information within organizations. We will discuss key elements of modern DLP, including data identification, data monitoring, and data protection techniques such as encryption, masking, and tokenization.

Next, we'll explore the latest trends in DLP, such as the significance of cloud DLP, the integration of AI and machine learning, and the importance of seamless integration with other security tools. We'll provide guidelines for effective data protection, including the development of robust data protection policies, the importance of employee training, and the necessity of regular security audits.

We will address common challenges in implementing DLP, such as complexity, cost, and the need to keep up with changing data protection regulations. Case studies will be presented, showcasing examples of companies that have successfully implemented DLP, highlighting their strategies and lessons learned from their experiences.

The future outlook of DLP will be discussed, covering emerging technologies and the evolving threat landscape, and how organizations can a

What attendees will learn:
- Understand the key components and strategies of modern Data Loss Prevention (DLP) and data protection techniques.
- Gain insights into the latest trends and best practices for safeguarding data, including AI integration and cloud security.
- Learn from real-world case studies and explore the future of DLP in the face of evolving threats and technological advancements