Why is UEBA the Lynchpin of Zero Trust Security?

Why is UEBA the Lynchpin of Zero Trust Security?

First coined in 2009 and based on the concept that trust is a vulnerability, Zero Trust (ZT) has emerged as a fundamental strategy for protecting sensitive data and systems. 

This approach continues to be focused on managing the complexities of user identities and access rights within organizations. ZT requires continuous verification of user access requests, minimizing the risk of security threats and lateral movement within the network. The architecture recommends a variety of tools like multifactor authentication (MFA), identity solutions like identity access management (IAM) and privileged access management (PAM), and network micro segmentation, designed to keep organizations safe from security threats. But an important gap is the part that UEBA should be playing in identity security and quantifying user risk. And according to Dark Reading, the US Navy is leading the way in addressing that. 

Why does UEBA matter to accomplishing Zero Trust? 

User and Entity Behavior Analytics (UEBA), a powerful tool that quantifies user risk. It improves on a Zero Trust security model by surfacing behavioral indicators of intent from individuals with permissions on the inside. With a continuous threat posture for every user based on behavioral risk scoring, UEBA helps defend ZT policies and enable organizations with risk-adaptive policy enforcement. Just because a user has verified access to data, doesn’t mean that users aren’t mistaken, compromised, or malicious. 

UEBA is indispensable to the Zero Trust model in 3 ways:

1. Quantification of User Risk

One of the primary functions of UEBA is to quantify user risk. This involves assessing the likelihood that a user’s behavior could pose a security threat. By analyzing behavior patterns such as login times, access locations, and the types of data accessed, UEBA assigns a risk score to each user. This quantification is crucial for several reasons:

• Proactive Threat Detection: High-risk users can be flagged for further investigation before they cause harm.
• Resource Allocation: Security teams can prioritize their efforts on the most significant threats, optimizing the use of resources.
• Policy Enforcement: Risk scores can be used to enforce security policies dynamically, such as requiring multi-factor authentication for high-risk users.

2. Behavioral Intent Identification

Understanding the intent behind user actions is a critical aspect of identity security. UEBA goes beyond simple anomaly detection by analyzing the context and intent of user behavior. For example, a user accessing sensitive data at unusual hours might be flagged, but if the behavior aligns with a legitimate business need, the risk assessment may be adjusted accordingly.

• Contextual Analysis: UEBA considers the context of user actions, such as the time of day, location, and the user’s role within the organization.
• Intent-Based Alerts: By identifying the intent behind actions, UEBA can differentiate between benign anomalies and genuine threats, reducing false positives and improving response accuracy.

3. Continuous Monitoring and Adaptation

Zero Trust requires continuous monitoring and adaptation to evolving threats. UEBA supports this by providing real-time insights into user behavior and adapting to new patterns over time. This dynamic approach ensures that security measures remain effective against emerging threats.

• Real-Time Insights: Continuous monitoring allows for immediate detection and response to suspicious activities.
• Adaptive Learning: UEBA systems learn and adapt to new behaviors, ensuring that the baseline of normal behavior remains accurate and relevant.

How can I accurately determine user intent?

Based on AI-driven behavioral science, DTEX collects a unique set of behavior-based metadata that extends beyond low level system data that other tools collect. The platform identifies patterns of related attributions that enables the identification of risky user activity sooner, before a breach. This includes:

• High Fidelity Metadata: DTEX collects higher user mode information, unique elements of enterprise telemetry to capture activity history, behavior trends, data utilization with situational context from across an organization’s estate to form a holistic understanding of risk. 
• Easy, Continuous Collection Without Triggers: The platform collects activity continuously, on and off network, whether it is interesting at the time or not. By collecting all activity, critical context is provided, elevating risks and insights more accurately. 
• More Insightful Baselines: DTEX goes deeper than ‘usual vs unusual’ behavior to focus on activities truly associated with data loss like reconnaissance, obfuscation and circumvention. It is important to understand all behavior for each user.
• Analytics with Multidimensional Risk Scores: DTEX provides a deeper approach to risk scoring, with enhanced contextual analysis and advanced risk modeling that identifies early indicator of intent and ultimately distinguishes between malicious, careless, and compromised users.

Conclusion

UEBA is designed to quantify user risk and identify behavioral intent but the quality of data matters. By continuously monitoring and analyzing user behavior, DTEX UEBA enhances identity security and ensures that organizations can proactively detect and deter risky users. As awareness grows around insider risk as a discipline, the role of UEBA in Zero Trust will become clearer, making it an essential component of modern cybersecurity strategies. To learn more, read UEBA’s Power in Insider Risk Management: Reactive to Proactive or request a demo.