UEBA vs. SIEM: What's the difference?

In today’s data-centric business landscape, organizations must take effective measures to protect their data resources and intellectual property from insider threats and external threat actors. Without adequate data security, organizations unnecessarily expose themselves to risk.

Multiple methodologies have been introduced in attempts to secure IT environments and the data they contain. Typically, a combination of techniques is required to provide an acceptable level of security. In this post, we'll discuss the differences between UEBA and SIEM and how the two approaches complement each other and promote security.

While UEBA (User and Entity Behavior Analytics) and SIEM (Security Information and Event Management) are both crucial components in the cybersecurity world, they serve different purposes and operate in distinct ways.

In this article:

Wh‎‎at is SIEM?

‎Security information and event management (SIEM) is a security management methodology that combines the functions of security information management and security event management into a unified system. SIEM systems collect, log, and aggregate data from multiple sources within the IT environment to identify abnormal activity and take appropriate action.

SIEM systems can be rule-based or employ an automated engine to find connections between multiple log entries. The actions may include generating alerts or prohibiting an activity from being performed. Organizations can set thresholds to minimize the volume of alerts generated by an SIEM tool.

Consolidating all security-related information to provide a unified perspective simplifies the task of identifying anomalous events. Unusual patterns of behavior are easier to detect when observing the environment from a single point of view.

SIEM benefits include:

Providing a holistic view of the complete IT environment
Reducing the time required to identify threats
Performing threat detection and forensic analysis
Supporting large volumes of data

Limitations of SIEM systems include:

It can take months to effectively implement a SIEM system.
Systems can be expensive to set up and maintain.
Experts are required to analyze SIEM reports.
Misconfiguration may lead to missed security events.

Wh‎‎at is UEBA?

User and entity behavior analytics (UEBA) involves the study of user and entity behavior in an IT environment to derive insights that may indicate the presence of a security threat. Insights are acquired by identifying suspicious or abnormal behavior. UEBA systems collect multiple types of data including user roles, data access, permissions, user activity, location, and security alerts.

UEBA tools create baselines to define normal activity in the environment, which it compares to monitored behavior. A UEBA system makes decisions and evaluates risks based on the sensitivity or resources involved in a particular activity. These tools also rate threats so security analysts can focus on more pressing issues. Machine learning (ML) is often incorporated into UEBA solutions to reduce false positives and continuously refine their reporting capabilities.

UEBA systems are typically effective in identifying these kinds of security issues:

Unauthorized data access
Data loss
Brute-force hacker attacks
Lateral movement throughout an IT environment
Suspicious behavior that may indicate malicious insider activity

UE‎BA vs. SIEM: Functional differences

Cybersecurity analyst team discussing critical events

‎SIEM and UEBA are both intended to furnish information that can be used to enhance an organization’s IT security. Some major differences in these methodologies exist and may influence decision-makers when choosing a security solution. In many cases, a combination of SIEM and UEBA provides the most effective cybersecurity.

The following are the main differences between SIEM and UEBA.

Data storage: SIEM systems typically store data for extended periods of up to a year or more and use that data to uncover patterns in IT activity. UEBA solutions rely on real-time or more recently collected data to identify abnormal behavior.
Rule-based vs. baseline: Most SIEM systems are rule-based which requires rules to be modified to reflect changes in the environment or acceptable user behavior. UEBA systems look for anomalies to the baseline that may or may not indicate malicious or risky behavior.
Data sources: SIEM systems primarily leverage the data from security device logs such as firewalls. UEBA investigates application logs as well to uncover suspicious behavior that may escape detection from an SIEM tool.
Data enrichment: UEBA can enrich data by including information on the user involved in the activity to better determine the severity of suspicious activity.
Rules evolution: UEBA rules evolve over time as data from more events is collected and used to modify threat evaluation.

A combination of SIEM and UEBA solutions offers organizations the most effective security.

In‎tegration and Complementarity

Integration: Often, UEBA capabilities are integrated into SIEM solutions to enhance their ability to detect advanced threats.

Complementarity: While SIEM provides a broad overview of security events and compliance, UEBA adds a layer of behavioral analytics that can identify more subtle and sophisticated threats that might not trigger traditional security alerts.

SIEM provides a comprehensive platform for security management including log aggregation, compliance, and event correlation, while UEBA adds a specialized focus on behavior analytics to detect anomalies that could indicate advanced threats, insider risks, or compromised credentials. Together, they offer a more robust defense against a wide range of security threats.

Ho‎‎‎w does data loss prevention work with SIEM and UEBA?

‎Data loss prevention (DLP) solutions support both the SIEM and UEBA approach to cybersecurity. Modern DLP software, such as the Reveal platform by Next, provides UEBA capabilities that complement an organization’s SIEM implementation.

The following features of Reveal make it an effective UEBA solution.

Its hybrid cloud and edge deployment options allow for scalable analysis and help reduce false positives.
The platform employs dual machine learning and dynamic analytics to create a baseline of what normal use behavior looks like so that it can identify and stop unique threats and attacks.
Adaptive learning is promoted through continuous recalibration and providing creative policy suggestions.
Reveal provides simple reports of security violations so controls can be assessed and modified as necessary.

Get in touch and schedule a demo to see Reveal in action and start taking proactive measures to secure your company's valuable data.

Fr‎‎equently asked questions

Which is a better security solution, SIEM or UEBA?

SIEM and UEBA solutions address the issue of cybersecurity using different approaches. UEBA tools can identify new threats more rapidly than an SIEM solution by interrogating activity in the environment against its baselines. This may make a UEBA platform more effective against the continuously evolving techniques and attacks perpetrated by threat actors.

Can UEBA systems identify all anomalous behavior?

A UEBA system may not be able to identify all anomalous behavior until it has developed a baseline against which to compare events in the IT environment. Tools that include pre-defined and configurable policies, like Reveal, allow organizations to achieve immediate benefits from the solution as it refines baselines and becomes more efficient at identifying suspicious activity.

What is the drawback of simply relying on rule-based systems such as SIEM?

The problem with rule-based SIEM systems is that the rules must be correctly updated to reflect changes in the environment or what is considered to be acceptable user activity. Failure to update the rules or misconfiguration issues may lead to missed security violations that pose a risk to an organization’s valuable data and systems.