Leveraging Anomaly Detection. To enhance our threat hunting capabilities, the Anitian SecOps team has invested in anomaly detection as a capability to surface subtle security risks and/or obvious ...

This continuous learning and adaptation are key. Now, let’s take a look at how Machine Learning can help when we’re dealing with ransomware. Applying Machine Learning Models to Ransomware Recovery ...

A growing number of research papers shed light on automated machine learning (AutoML) frameworks, which are becoming a promising solution for building complex machine learning models without human ...

We propose a framework for anomaly detection in communication network logs along with automated extraction of human-readable annotations that explain the decision logic underlying each anomaly ...

As machine learning models become widely applied in financial anomaly detection, the issue of model interpretability has become increasingly prominent. In the financial domain, understanding the ...

Normally anomaly detection takes time to set up. You need to train your model against a large amount of data to determine what’s normal operation and what’s out of the ordinary.

Anomaly detection is a machine learning task that aims to identify unusual or suspicious patterns in data, such as fraud, errors, or outliers. It can be useful for various applications, such as ...

A real strength of machine learning is that it enables humans to predict and proactively address potential dangers instead of dealing with them when the damage has occurred. As we’ve seen, machine ...