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, ...

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 ...

In today's digital landscape, organizations face an unprecedented challenge: managing and protecting ever-growing volumes of data spread across multiple environments. As someone deeply involved in ...

CIOs and IT directors working on any project that involves data in any way are always more likely to succeed when the organisation has a clear view of the data it holds. Increasingly, organisations ...

Purdue University academic and administrative data are important university resources and assets. Data used by the University often contains detailed information about Purdue University as well as ...

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 ...

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 ...

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 ...

If you’re a data person, or even if you’re not, you may have heard the statistic cited by Eric Schmidt, executive chairman at Google: “There were 5 exabytes of information created between the dawn of ...

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 ...

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 ...