How Splunk can help: Implementing advanced threat detection

Would security capabilities that help you focus attention towards malicious actions improve your detections? Would fewer alerts of more value give your team more time for better response? Would expanding machine learning capabilities give your security operations an advanced edge?

With Splunk Enterprise Security, you can leverage advanced capabilities faster and easier, rather than needing to build advanced detections from the ground up. These include:

• Risk-based alerting that allows the security domain to use fewer event criteria driven sources. This means that you have an advanced, fully operational detection and response framework in less time.
• A use case library that gives you analytic stories to build content from. Each of these comes with framework mapping to a variety of different kill chains and the MITRE ATT&CK framework.
• Recommendations for data sources, source types, and data models.
• The power of machine learning and streaming analytics with behavior analysis. Unsupervised machine learning algorithms analyze data and detect anomalies that deviate from normal behavior. This continuous learning process allows you to better adapt to emerging cyber threats.
• Visual threat topology that maps risk objects to associated threat objects.
• Reports that show a variety of threat sources with additional detail all within one place to enrich notable events and give more context.

To learn more, watch the following demo to see how alerting that is better focused on surfacing legitimate threats takes less time and is easier for teams to manage.