Data Segmentation & Isolation
Traditional clustering techniques often struggle to manage datasets containing both continuous and categorical variables, a challenge especially pronounced in clinical data. These datasets are often rich with diverse types of data, making the need for a versatile clustering algorithm paramount. The DAFI-Gower algorithm is designed to address this
In a bid to create a unified method for businesses to evaluate and secure their data, a national data classification framework has been initiated, marking a significant step forward in the national cybersecurity strategy. This groundbreaking initiative is spearheaded by the Australian Cyber Collaboration Centre (AusC3) with valuable support from
In a significant security overhaul, Microsoft has redesigned the Windows Recall feature, initially retracted following public backlash over privacy concerns. Windows Recall aims to create an AI-powered, searchable digital memory of user activity by capturing five-second snapshots of the Windows screen. However, concerns about potential security
Clustering analysis is a fundamental technique in data science, used to group similar data points together. However, traditional clustering methods often struggle with datasets that contain both continuous and categorical variables, a common scenario in real-world clinical data. This article explores a novel clustering technique, the DAFI-Gower
In today’s digital age, sensitive data is a lucrative target for cyberattacks and compliance violations, making its effective classification vital for safeguarding information. Understanding this, Intuit recently hosted its inaugural Data Classification Challenge, assembling 20 of the most advanced data security vendors from the U.S. and Israel.