Beyond UEBA: Elevating Insider Risk Management with Behavioral Intelligence

Key Takeaways:

• Evolving Beyond UEBA: Traditional UEBA alone often lacks the depth needed to tackle today’s complex insider threats effectively.
• Behavioral Intelligence Matters: Advanced IRM solutions monitor sentiment, disengagement, and data access patterns over time, capturing nuanced risks that basic log analysis misses.
• Real-Time, Dynamic Risk Profiling: Continuously updating user risk scores provides immediate insights, allowing teams to take proactive action on high-risk behaviors.
• Contextual Understanding: IRM tools add critical context to insider behaviors, helping security teams differentiate routine actions from true threats.

Advancing Beyond UEBA for Insider Risk Management (IRM)

Insider risk management is more critical than ever as human error and insider threats drive escalating security breaches. While many organizations have adopted User and Entity Behavior Analytics (UEBA) to monitor potential risks, relying solely on UEBA may fall short of the depth needed to stay ahead of these increasingly complex threats. To truly get ahead of risk, solutions must advance beyond traditional approaches, offering comprehensive behavioral intelligence that evolves alongside emerging security challenges.

The statistics underscore the urgency for more advanced solutions:

• According to Gartner, 90% of employees knowingly take actions that could jeopardize their organization’s security.
• IBM’s 2023 Cost of a Data Breach Report reveals that cyber-attacks initiated by malicious insiders were the most costly, averaging $4.90 million per breach—9.6% higher than the global average of $4.45 million.
• Verizon’s 2023 Data Breach Investigations Report further highlights the impact of human elements, showing that 74% of breaches involved a human component.

This blog will explore why UEBA alone may be insufficient for addressing today’s insider risks. We’ll also examine how emerging insider risk management platforms go beyond UEBA, providing the predictive insights, nuanced analysis, and proactive responses necessary to detect, analyze, and prevent insider threats.

The Limitations of UEBA

UEBA solutions are increasingly becoming a staple in advanced cybersecurity practices, offering the ability to detect behavioral anomalies and track activities such as:

• Logon events
• File access
• Data transfers
• Application usage

However, UEBA tools typically analyze second-hand data, such as system logs and event data, to flag suspicious behavior. While these tools can effectively identify abnormal patterns, they often cannot connect those events meaningfully, leaving security teams with partial insights into what might be happening.

For example, a UEBA tool might detect a series of failed login attempts or unusual logins from remote locations. Still, without more context, it may be challenging to determine whether these are legitimate mistakes or early indicators of insider threats. To identify risk, solutions must go beyond surface-level anomalies.

Going Beyond UEBA: Metrics That Matter

It’s essential to gain a more comprehensive approach to insider risk management by incorporating advanced behavioral intelligence, user activity monitoring, and continuously analyzing behavior changes over time, generating dynamic insights and risk profiles based on multiple metrics. Let’s look at the metrics that matter most when managing insider threats:

1. Language Sentiment with NLP

One fundamental limitation of UEBA is its inability to analyze the content of communications in real-time. Look for Natural Language Processing (NLP) to assess the emotional tone and sentiment behind emails, chats, and other communications. Negative sentiments, such as frustration or dissatisfaction, can be early indicators of disengagement or a potential insider threat. This added layer of behavioral intelligence goes beyond UEBA’s focus on activity logs, allowing you to identify potential risks before they escalate.

2. Disengagement and Retention Risk

Traditional UEBA tools track user and device activities, but they lack insight into changes in productivity and engagement levels. Look for continuous monitoring of behavior patterns—such as drops in activity or sudden changes in work habits—to flag individuals who may be at higher risk for insider threats, such as disgruntled employees or those planning to leave the company. These behavioral shifts are crucial in predicting insider risks and preventing drops in productivity, which are often missed by event-driven UEBA systems.

3. Sensitive Data Access

When UEBA detects file access and data transfers, it treats each event in isolation. Go a step further by analyzing patterns in how users interact with sensitive data over time. The latest platforms can detect when employees gradually increase their access to sensitive information, repeatedly accessing data they don’t usually work with or sharing protected data externally. By continuously assessing how users interact with sensitive data, IRM helps organizations maintain compliance with policies and regulations and can help trigger accurate alerts of potential risks.

4. Potential Fraud

UEBA tools often focus on flagging abnormal activities but may lack the ability to correlate various behavioral indicators, such as frequent attempts to access restricted files or suspicious communication patterns. By analyzing these seemingly unrelated events, IRM helps identify users attempting fraud or other malicious activities. These insights provide a much clearer view of the risk landscape, enabling security teams to take swift action.

Dynamic Risk Profiling and Real-Time Monitoring

Unlike traditional UEBA, which typically relies on fixed rules and thresholds, advanced security solutions can benefit from dynamic risk profiling that continually updates each user’s risk score. This approach flags high-risk behaviors immediately so security teams can act before issues escalate. Real-time monitoring of critical activities—like file transfers, network access, and communications—provides insights security teams need for well-informed responses.

By implementing dynamic risk profiling, you can detect nuanced risks that conventional UEBA tools might overlook, creating a proactive approach to insider threat management that’s adaptive to evolving behaviors and patterns.

Connecting the Dots: Move to Behavioral Intelligence

UEBA focuses on detecting anomalies through second-hand data. To provide context-based behavioral intelligence, first-hand contextual data should be integrated with existing security tools, such as SIEM, DLP, SOAR, and XDR. This gives security teams actionable insights to prioritize high-risk activities, reducing false positives and alert fatigue.

Real-Time Data vs. Event-Based Logs: While UEBA alerts are often reactive, IRM with behavioral intelligence delivers real-time monitoring and behavioral analysis so security teams can be proactive and focus on critical threats.

Why Veriato IRM is the Next Evolution of Insider Risk Management

While UEBA focuses primarily on detecting anomalies and flagging suspicious activities, Veriato Insider Risk Management offers a more comprehensive and proactive approach to safeguarding organizations. Here’s why:

Proactive Measures: IRM gets ahead of detecting threats after they occur—it provides the intelligence for organizations to initiate training, policy enforcement, and HR involvement as appropriate. This holistic approach helps organizations not only identify risks but also prevent incidents from occurring.

Contextual Understanding: IRM dives deeper into the motivations and behaviors behind insider threats. By understanding why employees or insiders might pose a risk, IRM provides more targeted, effective countermeasures, making it easier to take preventative actions before threats escalate.

Reduced Response Time: With real-time monitoring and dynamic risk profiles, IRM reduces the time it takes to detect and contain insider incidents. Formal IRM programs offer faster responses than traditional UEBA systems, minimizing potential damage.

Organization-Specific Strategies: IRM’s configuration flexibility allows organizations to fine-tune behavioral intelligence to focus on the alerts and triggers that matter most to their industry or role. It can be customized to detect compliance-related anomalies and adapt to make it an ideal tool for customized insider threat management for multiple industries.

In conclusion, while UEBA remains a valuable tool in detecting insider threats, IRM provides a more holistic, proactive, and tailored approach to managing risk. Using behavioral intelligence, real-time monitoring, and risk profiling, Veriato IRM allows organizations to detect, predict, and prevent insider threats before they escalate.

Learn more about Veriato IRM in our eBook: https://veriato.com/ebooks-whitepapers/irm-guide-predict-human-risk/

Contact us today to learn how Veriato IRM can transform your approach to managing insider risk.

FAQs

Q: What is the difference between UEBA (User and Entity Behavior Analytics) and advanced Insider Risk Management (IRM)?
A: UEBA focuses on identifying anomalies in user behavior by analyzing system logs and event data, often based on pre-set rules. Advanced IRM incorporates real-time behavioral intelligence, dynamic risk profiling, and contextual insights. IRM enables proactive threat detection by continuously monitoring behavior, emotions, and engagement changes, giving security teams a more nuanced understanding of potential risks.

Q: Why is traditional UEBA considered insufficient for managing insider threats?
A: While UEBA can detect unusual behaviors, it often lacks the depth to connect various risk indicators meaningfully. It mainly flags surface-level anomalies without understanding the broader behavioral context, making it challenging to assess intent. Advanced IRM integrates additional behavioral metrics and real-time analysis, allowing organizations to differentiate between routine anomalies and true insider threats.

Q: How does dynamic risk profiling enhance insider risk management?
A: Dynamic risk profiling continuously updates a user’s risk score based on their evolving behaviors. Unlike static thresholds, this approach adapts to real-time changes, allowing high-risk actions to be flagged immediately. This makes it easier for security teams to detect and respond to potential insider threats before they escalate, a capability that traditional UEBA systems generally lack.

Q: What behaviors or data does advanced IRM analyze that UEBA might miss?
A: Advanced IRM incorporates metrics such as language sentiment through NLP (Natural Language Processing), disengagement indicators, unusual access patterns to sensitive data, and potential fraud indicators. These insights provide a more comprehensive view of user behaviors, detecting risk signals like frustration, increased access to confidential files, or frequent attempts to bypass security protocols that UEBA may overlook.

Q: How does IRM’s integration with AI improve threat detection and prevention?
A: AI-driven IRM solutions analyze behavioral patterns over time, identifying subtle anomalies that might signal insider risks. This continuous analysis enables proactive threat detection, shifting organizations from reactive responses to proactive prevention. AI helps reduce false positives and alert fatigue by providing a clearer, more actionable picture of user behavior trends.

Q: Why is monitoring sentiment and engagement in insider risk management critical?
A: Changes in sentiment and engagement can signal potential insider risks, such as dissatisfaction, disengagement, or burnout. Monitoring these factors allows organizations to identify at-risk employees who may be more likely to act maliciously or negligently. This human-centric approach ensures that insider risks are addressed at their roots, helping organizations prevent incidents rather than simply reacting to them.

Q: How does real-time monitoring in IRM compare to UEBA’s event-based logging?
A: Real-time monitoring in IRM allows security teams to detect and respond to risks as they happen, providing immediate insights into user actions and potential threats. In contrast, UEBA’s event-based logging is often reactive, alerting teams after suspicious activities have occurred. Real-time IRM is thus more effective in preventing risks before they escalate.

Q: How can companies determine if they need to upgrade from UEBA to a more advanced IRM solution?
A: Companies should consider upgrading if they find that traditional UEBA lacks the depth needed to address complex insider threats, generates too many false positives, or fails to provide actionable insights. Additionally, organizations experiencing increased insider incidents or managing sensitive data would benefit from IRM’s enhanced behavioral intelligence and proactive capabilities.