Preventing known threats is no longer enough to keep you protected. The mere volume of logs and events often presents a significant challenge for security teams.
Through testing and research SkyePoint engineers recognized the advantages of strong ML concepts and developed an approach to leverage them through a collaborative effort between human analysts and AI. This results in a significant increase in the ability to obtain and identify potentially qualified data, allowing cyber analysts to better perform their analysis task to identify new and/or unique Threat Tactics, Techniques, and Procedures (TTPs).
Threat Predict addresses network monitoring and cybersecurity operational needs by using AI/ML to identify and respond to both known and unknown vulnerabilities and threats to enterprise environments. It pulls and processes an extraordinary amount of data, while at the same time limiting what your cybersecurity analyst must analyze. This proactively identifies and targets what needs to be reviewed and provides actionable intelligence that reduces the time and manpower needed to identify and respond to potential vulnerabilities and improves your organization’s Threat Hunt success.
View this on-demand recording to learn more about:
- The capabilities and current use cases for the Threat Predict technology solution
- The ways Threat Predict can help move your agency toward a zero-trust security framework
- How SkyePoint uses TIBCO Data Virtualization, TIBCO Spotfire, and TIBCO Data Science capabilities
- How to achieve a 30% increase in security operations center (SOC) analysis productivity by reducing the signal-to-noise ratio in security log data