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SIEM vs Security Analytics: What’s the Difference?

Solutions Review Presents: The Top Data Breaches of 2020
SIEM vs security analytics

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As dramatic as it sounds, comparing SIEM vs security analytics is a vital discussion for enterprises facing the multitudes of cybersecurity threats born from the modern age: hackers, insider threats, the weight of despair and hopelessness from users, regulatory compliance, etc.

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Every enterprise—of all sizes and industries—needs information security capabilities. Digital threats are increasing year after year, simultaneously growing in severity and sophistication. Yet the difference between security information and event management (SIEM) and security analytics can prove pedantic and frustrating for enterprises wading through all the cybersecurity jargon searching for a clear-cut answer.

Fortunately, we here are Solutions Review are on hand to help you distinguish the benefits of SIEM vs security analytics (or vice versa) and help your enterprise make the right information security selection.

SIEM vs Security Analytics: Two Peas in a Pod?  

Part of what can confuse so many enterprises trying to find the right solution is that in the debate of SIEM vs security analytics is that those variations can seem arbitrary or even non-existent on the surface.

Indeed, SIEM solutions and security analytics feature similar capabilities, including:

  • Log and Event Management
  • Behavioral Analysis
  • Data Correlation
  • Compliance Reporting
  • Security Event Data Compilation, Aggregation, and Analysis
  • Threat Hunting
  • Centralized Compliance Report Generation

Additionally, both SIEM and security analytics have similar priorities and security goals. With the digitization of business processes and the advent of digital transformation, enterprises can generate terabytes of security event data a month. This security event data is distributed throughout your IT environment, and the correlations between them—several failed logins from the same user, unusual behavior from that user, data flows moving in patterns that defy normal business processes—can indicate a security breach.

Your human IT security certainly can collect and aggregate all of this security information, analyze it for correlations, and investigate those correlations to determine if they are false positives or indicators of legitimate threats. However, doing so would be a severe drain on their time and resources that cannot be recouped.    

SIEM and security analytics improve the speed of accuracy of threat detection by conducting much of the security event correlation and analysis automatically. They seek to reduce the mean time to detect (abbreviated MTTD) and the mean time to respond (MTTR) to cyber threats via AI learning protocols like machine learning or user and entity behavior analytics (UEBA).

In other words, SIEM and security analytics make sorting through the gigabytes of enterprise data in real time easier than ever before. Yet both solutions require human knowledge and involvement to perform at optimal levels, which are unfortunately in high demand and limited supply, as both can fall prey to false positives.  

So if so much of this article highlights how similar the competitors of SIEM vs security analytics are, how do they differ?

It might be an indicator of the speed of cybersecurity development.

SIEM vs Security Analytics: One in the Same?

From our independent research, we’ve noticed something interesting. Many of the solution providers and vendors writing about the substantial differences between SIEM vs security analytics criticized SIEM as being unable to handle modern threats, limited to on-premises infrastructures and inflexible architectures, and limited threat hunting capabilities. They praise security analytics as being capable of UEBA, correlating identity across multiple systems, and being far more flexible in their data collection.

While this sounds like an indictment of SIEM, these same criticisms singled out legacy SIEM solutions. Indeed, maybe of the criticisms of legacy SIEM does not seem to correspond to the SIEM solutions currently on the market, which do feature UEBA and more expansive detection.  

It seems to us that legacy SIEM solutions are on the way out but that next-gen SIEM and security analytics perform nearly identical functions; we could even understand arguments stating that security analytics is another way of saying “next-gen SIEM.”

So in answering the debate of SIEM vs security analytics, we do recommend that enterprises review their SIEM solution to ensure they have one that best fits their needs and use-case and carefully examine the individual capabilities of potential solutions. This is a serious choice that could have long-term effects on your enterprise. Choose well!

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