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, ...

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 ...

The purpose of this standard is to assist Users, Stewards, Managers, and Information Service Providers in identifying what level of security is required to protect data for which they are responsible.

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 ...

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, ...

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 ...

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 ...

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 ...

New York, NEW YORK, June 11, 2026 (GLOBE NEWSWIRE) -- Teleskope, the first agentic data security platform today announced the Data Reasoning Layer, aiming to help security teams to protect data while ...

Imbalanced data classification is a challenging task in real applications. In this work. A method is proposed for image classification using imbalanced distribution of classes. The proposed method ...

Label-free imaging enables multidimensional data acquisition across spectral and temporal domains and is increasingly used in life sciences. However, users working with multidimensional label-free ...