SECURITY

Stop Security Threats With Real-Time Data Monitoring

Imagine having a vast library of books but not being able to see what words live on the page that you are reading or want to read. That would be like being able to ingest security relevant data from a diverse array of data sources but not being able to use that information to monitor your security posture in near real time.

Library of Congress

Library of Congress

Real-time data monitoring is essential to secure an enterprise because it gives security practitioners the ability to monitor and manage the consumption and use of machine data across complex IT and security systems with visual insights into that data. The data can come from sources such as web logs, application usage to digital transactions. Why does this matter?

For organizations using security information event management (SIEM) systems to protect their infrastructure, near real-time monitoring is the difference between having books and knowing what’s inside them cover-to-cover. Near real-time monitoring makes threat detection and rapid responses to breaches possible.

Event correlation take real-time monitoring further by establishing relationships among messages or events generated by devices, systems or applications, based on characteristics such as the source, target, and protocol or event type.

A SIEM solution with near real-time monitoring capabilities should have a library of pre-defined correlation rules and the ability for security practitioners to easily customize those rules. For example, correlation rules can be built interactively using a search bar and selectively adding, removing or clicking on terms within search results.

Unlike a legacy SIEM, an analytics-driven SIEM solution provides real-time correlation against any data set with real-time enrichment using look ups, historical and other data lakes, retrieval from both cloud or on premise systems and more. This opens up the ability to create block lists to alert security experts when a known threat is arising.

A primary distinction between a traditional SIEM and an analytics-driven SIEM solution is the ability to correlate over both real-time data streams and historical data already stored.  The same searches can be used to look at both. Also, if a threat is discovered in real time, the same search can be run over historical data to identify where else a threat may exist.

Are you interested in learning how machine data can support an analytics-driven SIEM solution and improve your security posture? See why Gartner named Splunk a leader for the fourth consecutive year.

Related:
Three Ways Machine Data Makes Your SIEM Better at Security
Make Security Incidents Less Scary By Organizing Your Response

Girish Bhat
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Girish Bhat

Girish Bhat is the director of security product marketing at Splunk with responsibility for key security solutions, the Splunk CISO customer advisory board and customer use cases.

Previously, Girish held various roles managing authentication, compliance, VPN, advanced threats, DLP, IDS/IPS, mobile, SaaS, IaaS, virtualization and network monitoring solutions.

With more than 15 years of experience with startups and global brands, Girish’s experience includes product marketing, business strategy, strategic analysis, solutions marketing, product management for security, mobile, networking, cloud and software products.

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