In an era where sensitive data is a prime target for cyberattacks and compliance violations, effective data classification is the critical first step in safeguarding information. Recognizing the ...

The University at Buffalo (UB, university) has legal and ethical obligations to ensure that all forms of university data are adequately secured to minimize the risk of unauthorized use or disclosure.

Title: Data Classification and Protection Policy Effective Date: 2010 Responsible Office: Information Technology, Provost Last Revision Date: April 15, 2025 This document defines the William & Mary ...

Nevada Unveils New Statewide Data Classification Policy Months After Cyberattack Nevada’s IT agency has rolled out a new policy aimed at standardizing the privacy of state data, months after a massive ...

The study of clustering and classification of uncertain data addresses the challenges posed by imprecise, noisy, or inherently probabilistic measurements common in many modern data acquisition systems ...

UAB IT worked closely with information security officials from UAB Health System to develop the three level data classification system for all data. This system establishes roles and responsibilities ...

An effective data loss prevention (DLP) strategy is essential for protecting your organization's data, but without proper data classification, even the best DLP tools can fall short. Data ...

Conducting health equity research relies on complete, accurate information about race and ethnicity. However, data quality issues, including race/ethnicity misclassification and data incompleteness, ...

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 ...

This Policy serves as a foundation for the University’s data security practices and is consistent with the University’s data and records management standards. The University recognizes that the value ...