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.

Machine Learning Can Use Tweets to Spot Critical Security Flaws Researchers built an AI engine that uses tweets to predict the severity of software vulnerabilities with 86 percent accuracy.

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 ...

Machine learning will make sense of the security threats your organization faces and help your staff focus on more valuable, strategic tasks. It could also be the answer to the next WannaCry.

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 ...

This new advanced security integration between Hugging Face and JFrog differs from existing ML model scanners due to JFrog’s malicious code decompilation and deep data flow analysis.

Using a combined approach that saw the company engage with log data from version management vendor Perforce and analytics vendor Interset, the company got to work crunching the data they had.