In this talk, I will present an AI-driven, adaptive data security framework designed to protect modern databases in real-time. Traditional security approaches often fail to dynamically respond to evolving threats, leading to increased risk and delayed mitigation.

This session introduces a semantic-aware and feedback-driven architecture that leverages machine learning to detect anomalies, prevent unauthorized access, and minimize data breaches across platforms such as SQL, Oracle, DB2, and cloud databases.

Attendees will learn how AI enhances data protection, improves system performance, and enables proactive threat mitigation in enterprise environments.

Key Takeaways:

1. Understand limitations of traditional database security models
2. Learn how AI enables real-time threat detection and response
3. Explore semantic-aware security architecture for modern systems
4. Gain insights into performance optimization and risk reduction
5. Discover practical implementation strategies for enterprise environments