The purpose of this standard is to provide the University community with a framework for securing information from risks including, but not limited to, unauthorized use, access, disclosure, ...

This document defines the Cal Lutheran data classification scheme and establishes rules and procedures for protecting sensitive and protected university data processed, received, sent or maintained by ...

When it comes to managing data, we need to know where it is – but we also need to know what it is. With the rise in regulatory controls, enterprises now pay more attention to data sovereignty, ...

The University at Buffalo, (UB, university) classifies data into three risk-based categories to regulate access to, use of, and necessary precautions required to the protect university data. This ...

Data classification is an essential pre-requisite to data protection, security and compliance. Firms need to know where their data is and the types of data they hold. Organisations also need to ...

Data classification may not be a new concept, but it is a crucial one in the information security landscape. It’s vital because once you classify data into its type, level of access, and protection ...

The addition of LLM to Sentra’s classification engine allows scanning and classifying sensitive enterprise data like source codes, and employee details. Classifying sensitive unstructured data like ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...

UB classifies data into three risk-based categories to regulate access to, use of, and necessary precautions required to the protect university data. This policy provides a classification framework ...