Machine learning offers a way to improve anomaly detection operations to reduce the total risk for state and local governments. Stewart highlights the emerging process of encrypted data analytics.

A sample network anomaly detection project Suppose we wanted to detect network anomalies with the understanding that an anomaly might point to hardware failure, application failure, or an intrusion.

Leveraging machine learning There are different ways to address the challenge of anomaly detection, including supervised and unsupervised learning.

These outcomes are based on internal operational experience and are in line with efficiency gains often cited in broader ...

Datadog, the essential monitoring service for modern cloud environments, today announced the release of a new machine-learning based feature called An ...

Microsoft is extending its Azure Stream Analytics tool set with anomaly detection capabilities, powered by Machine Learning. For those curious to try, it is available now in private preview.

The three steps to better bot detection using AI and machine learning include analyzing all available data in the Identity Trust Global Network, using AI and machine learning to detect suspicious ...

Technologies like Azure Machine learning can leverage supervised learning techniques to help make business decisions based on classification, regression, and anomaly detection.