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The importance of event correlation techniques in SIEM

Event correlation tools are a fundamental instrument in your toolbox to detect threats from all sources across your organization in real time. A wise use of the right event correlation techniques through log management and analysis is the cornerstone of any reliable security information and event management (SIEM) strategy – a strategy that focuses on prevention rather than reaction. It represents the most efficient approach to root-cause analysis (RCA) that many IT departments now include in their performance monitoring best practices. Software capable of performing event correlation can ingest logs from infrastructure and make sense of correlated events to identify threat patterns and relationships across hundreds of events.


Event correlation is a powerful force to make log management much more efficient. Today, the volume of data generated by the countless events spanning across a network from routers, applications, and IoT devices is too massive for human beings to be kept track of. Data is thus extracted from centralized host logs or application logs and analyzed to identify recurring patterns which may have a significance. For example, a tool that uses event correlation can be used to enhance the ability to detect security breaches or send alerts for application or hardware failures that require the attention of the IT department.

For machines to be able to make sense of all this information, however, rules must be set, usually in the form of pre-specified sequences of events that can trigger an alert. Once these user-defined rules are set, event correlation tools will identify any potential threat in a very efficient way, correlating data from all sources in a single, organized, and streamlined screen. There’s no need to explain how being able to track down the source of a maintenance problem or security threat in real time and with no data losses, can minimize any business impact by a substantial margin.

The importance of centralized logs for event correlation engines

A quick and detailed analysis of event logs is mandatory for efficient RCA, but logs are not worth much if they’re kept isolated. The over-complicated relationship of the many events occurring across a network may make identifying a given threat pattern impossible when logs come from different sources and databases. For example, some logs cannot be directly read by humans while others must be encrypted for privacy reasons, or they may come in all formats, ranging from Excel, PDF, or plain text files. Log recorded with different formats cannot be analyzed side-by-side, and with no tool to parse patterns among static entries, every event recording must be debugged before it can be put up in a GUI.

If logs are collected from different source points, RCA will be slowed down to a crawl. To successfully detect anomalies in a network, the correlation of logs and their collection requires a systematic approach as well as an analytical architecture that reduces deployments. Think of a log that describes the detection of an “unauthorized access” event. Without a proper centralization tool, that log is not enough to establish whether the breach was caused by an external or internal source, and the real extent of the damage is impossible to ascertain. Centralizing log collection with a log management software such as Graylog means providing an event correlation tool with highly useable pre-digested logs that already possess the necessary correlation rules in them. Event correlation will then help follow the trail of the incident, and point the investigators from the IT department in the right direction.

What’s the added value of Graylog in event correlation techniques?

Graylog is easily the fastest, most flexible, most refined solution on the market to drive log ingestion and analysis to the next level. Since it supports distributed architectures, queries can be routed across systems, making the whole log ingestion process extremely quick and streamlined. When an incident occurs, time is of the essence, and software that allows you to analyze mass amounts of data in milliseconds is vital.

In particular, when text parsing comes into play, Graylog’s performance shines over its current competitors. By dividing vital unstructured data into logical categories such as time of the event, IP address, etc., Graylog can help IT teams parse data rapidly and intuitively and provide them with useful insights in real time. The easier is to make sense of this information in a timely fashion, the higher the chances to respond to any given challenge. Graylog uses Grok and Regex (regular expressions) to make parsing a much simpler task, and help even less-experienced admins get the insights they need with almost no delay even on day one.


The use of event correlation techniques is not a trend or fad, but an incredibly useful and practical approach to convert raw data into actionable insights. From improving security against intrusion detection to enhancing system optimization or connecting the dots in network forensics, log correlation holds a lot of value in many different scenarios.

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