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 ...

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 ...

Data security solution startup Metomic Ltd. today announced a new solution that makes it possible to discover, classify and secure sensitive data at large scale across Google Workspaces. The new Data ...

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, ...

Here's a complete end-to-end demo of what Dr. James McCaffrey of Microsoft Research says is arguably the simplest possible classification technique. The goal of a machine learning classification ...

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 ...

A data storage strategy that addresses data sovereignty builds on the classification of data in the data audit to limit what data can go where. As part of the classification process, data will be ...

Information technology and data constitute valuable Connecticut College assets. The purpose of data classification is to identify college data and it’s sensitivity. In order to protect the security, ...

Risk Description: Involves data that poses a reasonable risk and may lead to civil liability. Often tied to contracts or regulatory compliance. Data Types: Individually identifiable, confidential, ...