Table of Contents
What Is UEBA?
User and Entity Behavior Analytics (UEBA) is a cybersecurity process that uses machine learning, algorithms, and statistical analyses to identify when a user or machine’s behavior significantly deviates from established norms. It is an advanced method of detecting threats that traditional security tools may not catch. This technology is particularly effective at identifying and predicting risky user behavior and detecting malicious insiders, compromised accounts, and advanced persistent threats.
UEBA is not a standalone solution but rather a powerful addition to a company’s broader security ecosystem. It enhances other security measures by providing deep visibility into user activities, enabling security teams to identify subtle changes in behavior that may indicate a security threat. The system can track, collect, and analyze user behavior and other entity activities within a network, making it an essential tool in today’s advanced threat landscape.
The concept of UEBA is based on the premise that human behavior is consistent. In the context of network security, this means that users typically access the same servers and services, perform similar types of tasks, and follow other predictable patterns related to their roles. When these patterns change, it may be a sign of a security threat, prompting further investigation by the security team.
How UEBA Works
Data Collection
The first step in the UEBA process is data collection. This involves gathering data about user and entity behavior from various sources within a network. Sources can include log files, flow data, packet content, and other relevant information from network appliances and endpoints. The data collected will provide a comprehensive picture of the typical behavior of users and entities within the network.
Data collection in UEBA is not limited to network activity alone. It also includes other relevant information such as physical access logs, HR records, and external threat intelligence feeds. The more diverse the data sources, the more accurate the behavioral profiles that UEBA solutions can create.
Profile Building
After data collection, UEBA solutions proceed to the profile building phase. This involves analyzing the collected data to establish normal patterns of behavior for each user and entity. These patterns form a baseline against which future behavior can be compared.
Profile building is a continuous process in UEBA. The system constantly updates these profiles as it gathers more data and learns more about the users and entities. This continuous learning enables the system to adapt to changes in the environment and maintain accurate and up-to-date profiles.
Behavior Analysis
Once the profiles are established, UEBA solutions begin the behavior analysis phase. This involves monitoring user and entity behavior in real-time and comparing it to the established profiles. The system uses advanced algorithms and statistical models to identify significant deviations from the norm.
Behavior analysis is not just about identifying abnormal behavior. It also involves determining the risk associated with the behavior. For example, a user accessing a server for the first time may be considered abnormal, but it might not be risky if the user has the necessary permissions. On the other hand, a user attempting to access a high-value resource for which they have no business need could be considered both abnormal and risky.
Threat Detection
When the UEBA system identifies abnormal and risky behavior, it proceeds to the threat detection phase. This involves using the identified behavior and other contextual information to detect potential security threats.
Threat detection in UEBA is based on the risk associated with the behavior rather than the behavior itself. This makes it particularly effective at detecting advanced threats that traditional signature-based detection tools might miss. UEBA solutions can detect a wide range of threats, including insider threats, compromised accounts, and advanced persistent threats.
Alerts and Responses
The final phase in the UEBA process is alerts and responses. When a potential threat is detected, the UEBA system generates an alert and forwards it to the security team for investigation. The alert includes details about the abnormal behavior, the risk associated with it, and other relevant information that can help the security team respond effectively.
In addition to generating alerts, some UEBA solutions also provide automated response capabilities. This can include actions such as blocking a user’s access, isolating a system, or even initiating a full incident response process.
Advantages of UEBA
Early Detection
One of the key advantages of UEBA is its ability to detect threats early. By continuously monitoring user and entity behavior and identifying deviations from the norm, UEBA solutions can detect potential threats in their early stages, often before they have caused significant damage. This early detection capability can significantly reduce the impact of a security incident and improve an organization’s overall security posture.
Insider Threat Detection
UEBA is particularly effective at detecting insider threats. These threats, which involve malicious or negligent actions by employees or other insiders, are often hard to detect with traditional security tools. However, because UEBA focuses on user behavior, it can identify changes in behavior that may indicate an insider threat.
Reducing False Positives
Another advantage of UEBA is its ability to reduce false positives. Traditional security tools often generate a high number of false positives, which can overwhelm security teams and lead to real threats being overlooked. UEBA, on the other hand, uses advanced analytics and risk scoring to reduce the number of false positives and focus on the most significant threats.
Scalability
Finally, UEBA offers excellent scalability. As an organization grows and its network becomes more complex, the volume of security data can become overwhelming. UEBA solutions can handle this increased volume and complexity, making it a viable option for large organizations and those experiencing rapid growth.
Complementary Technologies for UEBA Integration
Identity and Access Management (IAM)
IAM serves as the foundation of an organization’s cybersecurity strategy. It allows businesses to manage the roles and access privileges of individual network users and the circumstances in which users are granted or denied those privileges. IAM systems ensure that access privileges are granted according to one interpretation of policy and all individuals and services are properly authenticated, authorized, and audited.
IAM’s integration with UEBA allows for a more intelligent and adaptive cybersecurity approach. UEBA, with its focus on behavioral patterns, leverages IAM to identify anomalies that deviate from normal user behavior. For instance, if a user suddenly accesses a sensitive system or information for which they don’t have regular access, IAM integrated with UEBA can flag this behavior for further investigation.
Moreover, IAM provides the context needed for UEBA to make sense of user activities. It gives UEBA the necessary user identity and access data, enabling the latter to construct a comprehensive picture of normal user behavior. With this integration, UEBA has a broader context for detecting suspicious activities, making it a more effective tool in preventing security breaches.
Security Information and Event Management (SIEM)
SIEM involves collecting, storing, aggregating, and analyzing logging data to identify and report on cybersecurity threats and incidents. It provides real-time analysis of security alerts generated by applications and network hardware.
Incorporating UEBA with SIEM takes threat detection to a new level. Traditional SIEM systems rely on predefined rules and correlation capabilities to identify threats. However, with the integration of UEBA, these systems can now incorporate behavioral analytics into their detection mechanisms. This combination allows the system to identify threats that traditional SIEM might miss, such as insider threats or slow and low attacks.
Moreover, the integration of UEBA with SIEM enables organizations to reduce false-positive alerts. UEBA’s behavioral analytics capabilities can analyze SIEM event data in the context of normal user behavior, reducing the likelihood of identifying non-threatening activities as potential threats. This leads to more accurate threat detection and saves valuable time for security teams.
Data Loss Prevention (DLP)
DLP technologies are designed to detect potential data breaches or exfiltration transmissions by monitoring, detecting, and blocking sensitive data while in use, in motion, and at rest. They help to ensure that end users do not send sensitive or critical information outside the corporate network.
The integration of UEBA with DLP provides a powerful tool for identifying anomalous behavior that may signal a data breach. UEBA can analyze the behavior of users and entities, identifying activities that deviate from the norm. When integrated with DLP, it can pinpoint suspicious activities involving sensitive data, such as unusual data access or transmission patterns.
Moreover, UEBA can enhance DLP’s effectiveness by providing context to data activities. It can identify whether particular data activities align with a user’s normal behavior or whether they indicate a potential threat. This can help organizations prioritize their response to potential data breaches, focusing their efforts on the most critical threats.
Endpoint Detection and Response (EDR)
EDR is a cybersecurity technology that addresses the need for continuous monitoring and response to advanced threats. It provides the tools needed to detect, investigate, and respond to advanced threats that may evade traditional security solutions.
When integrated with UEBA, EDR can become an even more powerful tool in an organization’s cybersecurity arsenal. UEBA can provide behavioral insights into endpoint activities, identifying anomalies that may indicate a threat. This can enhance the accuracy and speed of EDR’s threat detection capabilities.
Furthermore, UEBA can provide context to endpoint activities, helping to distinguish between normal and suspicious behavior. This can enhance the effectiveness of EDR’s threat response capabilities, helping to ensure that organizations focus their efforts on the most serious threats.
In conclusion, UEBA is a powerful tool in its own right, but its effectiveness can be significantly enhanced when integrated with complementary technologies like IAM, SIEM, DLP, and EDR. By leveraging these technologies, organizations can develop a more comprehensive and effective approach to cybersecurity.