AI-based data security management involves using machine learning algorithms to analyze data and detect patterns that may indicate potential security threats. The potential applications of AI in data security management include the automatic identification and classification of sensitive data and the use of natural language processing (NLP) to identify potentially sensitive information in unstructured data sources such as emails or documents. This can help organizations expand and improve their data protection measures and reduce the risk of data breaches.

This Session will focus on how information security governance personnel should use data maps to take stock of the data within an organization, and how machine learning can address the pain points encountered during traditional data inventories. It will cover the construction of data fortresses and the use of automated methods for data encryption, access control, compliance management, and leak prevention.