But machine learning is not a one-size-fits-all approach to log-data analysis. Different machine-learning techniques are suited to different types of log data and to different analytical challenges.

Logz.io offers a hosted service which performs intelligent log analysis by using machine learning to derive insights from human interactions with log data that includes discussions on tech forums ...

As the volume of cyberattacks grows, security analysts have become overwhelmed. To address this issue, developers are showing more interest in using Machine Learning (ML) to automate threat ...

All the threats were found in real-time using native machine learning and behavioral analytics. This type of analytics shows the value of both machine learning and the capturing of log data.

Human-aided machine learning “Machine learning is a critical component to developing Artificial Intelligence for IoT security,” says Uday Veeramachaneni, co-founder and CEO at PatternEx.

AI and machine learning are improving cybersecurity, helping human analysts triage threats and close vulnerabilities quicker. But they are also helping threat actors launch bigger, more complex ...

No matter the type of fraud, machine learning is a powerful tool to keep it from becoming a serious problem — regardless of how our circumstances may change.

At the National Security Agency, machine learning finds patterns in the mass of signals intelligence collects from global web traffic.