Unless you are successfully collecting and analyzing data from across your environment, you likely aren’t detecting and surfacing dangerous threats. And if you aren’t doing these things well, your mean time to detect and respond to threats likely is putting you ill at ease.
In the Threat Lifecycle Management (TLM) Framework, the Discover phase focuses on rapid threat detection and incident response through a blend of search and machine analytics.
If your security information and event management (SIEM) solution is surfacing noisy, meaningless alarms, your team can’t possibly focus on what is important. But by using machine analytics to realize a risk-based monitoring strategy that automatically identifies and priorities attacks and threats, your team can quickly investigate true threats.
Powered by people and enabled by technology, your team performs search analytics to actively hunt for threats. While effective, search analytics is people intensive, so it cannot be the sole method of analytics for an effective team.
Using machine learning and automation, machine analytics is performed by software for modern and efficient threat detection via data science-driven approaches so your team can focus their capabilities on your highest-risk issues.
Effective incident response requires having the right data to perform accurate analytics to determine which incidents are true threats. The LogRhythm Threat Lifecycle Management Platform captures high-quality data across your holistic environment. LogRhythm’s broad set of security analytics tools enable corroboration of this data to surface and detect real threats to your organization.
Learn more about how security analytics can advance your threat detection. Download our Definitive Guide to Security Intelligence and Analytics.
See how Sera-Brynn, a Top 10 cybersecurity audit and advisory firm, advanced their threat detection and incident response capabilities.