What is UEBA?

User and Entity Behavior Analytics (UEBA)  is a cybersecurity solution leveraging algorithms and machine learning to identify deviations in the behavior not only of users within a corporate network but also of the network’s routers, servers, and endpoints.

The aim of UEBA is to detect any unusual or suspicious activities, indicating deviations from typical usage patterns. For instance, if a user typically downloads 20 MB files daily but suddenly starts downloading 4 GB files, the UEBA system would flag this as an anomaly. It would then either notify an IT administrator or, if automated processes are enabled, disconnect the user from the network.

UEBA extends its monitoring beyond human behavior to include machine behavior. For example, if a server in a particular branch office experiences an unexpected surge in requests, potentially indicating a distributed denial-of-service (DDoS) attack, UEBA would promptly recognize this and initiate appropriate actions, even if IT administrators might overlook such activity.

How UEBA Works

For UEBA to effectively safeguard an organization, it must be deployed across all devices utilized by employees, whether owned by the company or the individual. Even devices used intermittently present potential targets for cyber threats. Some organizations may extend this coverage to employees’ home routers, recognizing them as potential entry points for attacks when connecting to the corporate network.

Upon installation, the UEBA solution enters a “silent” phase, gathering data on device and network activities. During this learning phase, its algorithms establish norms and optimal behaviors. IT administrators can set the duration of this phase before transitioning to testing mode.

A comprehensive UEBA solution comprises three key components:

• Analytics: This component organizes and analyzes data to establish baseline behaviors for users and entities. It creates profiles detailing typical application usage, communication patterns, download activity, and network connections. Statistical models are then employed to detect deviations from these norms.
• Integration: Seamless integration with existing security infrastructure is essential for organizations as they expand and adapt. Since many organizations already utilize security stacks, including legacy systems, UEBA complements rather than replaces these. By integrating data from various sources such as logs, packet captures, and other datasets, UEBA enhances the overall security posture.
• Presentation: This aspect involves conveying the UEBA system’s findings and determining appropriate responses. Procedures vary among organizations; some systems generate alerts for further investigation by either employees or IT personnel. Others are configured to take immediate action, such as suspending network access in response to suspected cyber threats.

Benefits of User and Entity Behavior Analytics

The surge in UEBA’s popularity arises from the realization that traditional security tools like web gateways, firewalls, intrusion detection, and encryption (such as VPNs) are insufficient to shield organizations from intrusion. Cyber attackers, increasingly sophisticated, can breach systems despite these measures, making the detection of even minor anomalies crucial.

Social engineering and phishing attacks are also on the rise, targeting people rather than hardware. By coaxing employees into clicking on links, downloading software, or revealing passwords, attackers can launch extensive cyber assaults starting from just one compromised device. UEBA aims to identify even the slightest unusual behavior, preventing minor phishing attempts from escalating into major data breaches.

Truly, UEBA can profoundly impact an organization’s security stance. Let’s delve deeper into its benefits and why companies should contemplate its adoption.

Expands Detection Capabilities

UEBA offers the significant advantage of broadening an enterprise’s ability to identify various cyber threats. From brute-force attacks to DDoS incidents, insider risks, and compromised accounts, UEBA covers a wide spectrum of potential dangers.

This efficacy stems from the fact that UEBA doesn’t solely focus on monitoring human actions on devices; it also encompasses the surveillance of the devices themselves. This includes servers, routers, endpoints, and Internet-of-Things (IoT) devices. With cyber threats becoming more diverse and sophisticated, attackers often find it easier to compromise a device directly rather than extracting information from human users.

As the prevalence of device usage increases—fewer printers or fax machines and more reliance on laptops and smartphones for work tasks—malicious actors are increasingly targeting devices, expanding the number of potential threat vectors exponentially.

Reduces Dependency on IT Analysts

The integration of machine learning and artificial intelligence in UEBA applications streamlines operations, potentially reducing the need for extensive human intervention. While this may cause concern among IT professionals, it doesn’t necessarily translate into a significant reduction in staff numbers. There are two main reasons for this:

Larger organizations, particularly multinational corporations and government entities, recognize the necessity of additional IT personnel and security analysts to set up, configure, and oversee the system, as well as to communicate regularly with employees.

If the organization opts not to implement automated response capabilities and instead prefers manual investigation of unusual behavior before taking action, additional security analysts may need to be deployed to the employee or device location.

Moreover, if the organization finds that fewer IT analysts are needed once the UEBA system is operational, these staff members can be reassigned to other high-priority projects.

Decreases Expenditure

Continuing from the previous point, if the organization requires fewer analysts to perform tasks handled by the UEBA system, it can lead to reduced IT spending. However, this doesn’t imply that the entire security analyst team should be terminated upon system implementation, as human intervention remains crucial in machine learning environments.

Furthermore, preventing a ransomware attack can be seen as a cost-saving measure. By averting the need to pay cyber attackers for system restoration or mitigating the loss of productivity caused by a malware-induced server outage, UEBA can yield significant financial benefits.

Mitigates Risk

The principal advantage of UEBA lies in risk reduction. While conventional security measures offer some level of protection, they have limitations. Modern organizations face a multitude of evolving threats, compounded by the proliferation of devices and locations. As remote work becomes commonplace, employees connect to corporate networks via various devices and routers accessing the public internet.

UEBA not only extends its coverage to employees’ home devices but also encompasses IoT and rugged devices deployed in diverse environments such as retail stores, warehouses, and hospitals. Any device linked to a corporate network presents a potential vulnerability. Given the impossibility for even large IT teams to physically monitor every device in use, UEBA significantly reduces this burden.

Importantly, UEBA serves not only as a threat detection tool but also as a compliance enforcer. Regulated industries like finance and healthcare have strict security standards that organizations must adhere to. While basic network monitoring tools can ascertain software updates, UEBA offers deeper insights. Detecting behavioral anomalies enables IT teams to address compliance issues promptly, potentially averting fines or legal proceedings associated with breaches.

However, there are drawbacks to acquiring and implementing UEBA systems, primarily concerning cost. The sophistication of UEBA, beneficial for large corporations with complex security needs, may prove prohibitive for smaller businesses. These organizations might find sufficient threat detection and management through alternative solutions like web gateways, firewalls, and VPNs.

UEBA vs. SIEM

Security Information and Event Management (SIEM) encompasses a sophisticated array of tools and technologies aimed at providing organizations with a comprehensive overview of their IT security landscape. It leverages data and event information to offer insights into typical patterns and issues alerts when anomalies occur. SIEM shares similarities with UEBA in utilizing user and entity behavior data to discern normal from abnormal activities.

SIEM serves as a foundational tool for security monitoring and analytics, gathering data from sources like firewalls, operating system logs, and network traffic. This raises the question: Is there a need for both SIEM and UEBA, or do they overlap significantly?

The answer lies in their distinct functionalities. Although they may appear similar, they serve different purposes.

SIEMs excel as security management platforms but may lack the sophistication required for advanced threat detection and response. While they can handle real-time threats effectively, they may struggle to detect sophisticated cyberattacks. These attackers often employ prolonged strategies that evade detection by conventional threat management tools for extended periods.

Conversely, UEBA solutions specialize in detecting complex threats, including those that may evade detection on a daily basis but reveal unexpected patterns over time. An example is malvertising, seemingly harmless advertising content that, over time, gathers user data or infects devices.

By integrating UEBA and SIEM tools, organizations enhance their ability to combat diverse threats. UEBA focuses on user or entity behavior, building profiles based on usage patterns and issuing alerts for unusual or suspicious activities. While SIEM excels in compliance reporting and event monitoring, UEBA is better suited for detecting insider threats and safeguarding high-value digital assets, particularly intellectual property (IP).

Before investing in both systems, it’s essential to evaluate the capabilities of existing SIEM systems, particularly in user monitoring, profiling, and anomaly detection, to determine if they align with your requirements before considering a UEBA solution.

Both SIEM and UEBA offer vital capabilities for meeting business and security objectives. Given the reality and costs associated with insider threats, considering UEBA as a complementary tool to SIEM is prudent.

UEBA vs. NTA

Network Traffic Analysis (NTA) solutions leverage machine learning, advanced analytics, and rule-based detection to monitor and analyze all traffic and flow records on enterprise networks. NTA systems are also adept at identifying potential threats and suspicious activities. So, how does NTA differ from a UEBA solution?

NTA offers several benefits. Firstly, it provides companies with visibility into all events occurring across their entire network, not just logged events, which includes every aspect of a cyber attacker’s activities. Additionally, NTA enables the profiling of both user accounts and network devices, similar to UEBA, and it is relatively straightforward to deploy.

However, like SIEM, organizations with more complex security needs will likely require both NTA and UEBA solutions concurrently. NTA is unable to track local events, such as those from a device not connected to the network, and generally lacks the capability to identify more advanced security issues in the same way that UEBA can.

UEBA vs. UBA

UEBA differs from User Behavior Analytics (UBA) by including an additional “E” in its acronym, which represents entities encompassing devices and applications. Therefore, UEBA is a more comprehensive version of UBA because it extends monitoring to nonhuman processes and machine entities, such as routers, servers, and endpoints or devices.

Gartner, a technology industry analyst firm, introduced the “E” in October 2017 to emphasize to the security industry that profiling entities beyond users is essential for accurately identifying threats.

Both user and entity activities are interconnected since devices are linked to routers. Other entities that require tracking include managed and unmanaged endpoints, various applications (cloud-based, mobile, and on-premises), networks, and the threats themselves.

Consequently, the inclusion of the “E” makes entity monitoring more inclusive and expands the scope of UEBA compared to standard UBA.

FAQ’s

What is UEBA and how does it differ from UBA?

UEBA stands for User and Entity Behavior Analytics, while UBA stands for User Behavior Analytics. The key difference lies in the inclusion of the “E” in UEBA, which represents entities such as devices and applications. UEBA offers a more comprehensive approach by monitoring both user and nonhuman behavior within a network.

Why is the inclusion of entities important in UEBA?

The inclusion of entities expands the scope of monitoring beyond human behavior to encompass devices and applications. This provides a more holistic view of potential threats within an organization’s network, as malicious activities can originate from both users and nonhuman sources.

How does UEBA contribute to cybersecurity?

UEBA leverages algorithms and machine learning to detect deviations in behavior across users and entities within a network. By identifying unusual or suspicious activities, UEBA helps organizations mitigate cybersecurity risks and prevent potential threats before they escalate.

Can UEBA be deployed across all devices within an organization?

Yes, for UEBA to be effective, it should be installed on all devices used by employees, including both company-owned and personal devices. This ensures comprehensive monitoring and protection against cyber threats across the entire network.

What are the key components of a UEBA solution?

A comprehensive UEBA solution typically includes analytics, integration, and presentation components. Analytics organizes and analyzes data to establish baseline behaviors, integration ensures seamless compatibility with existing security infrastructure, and presentation communicates findings and initiates appropriate responses.

How does UEBA complement other cybersecurity solutions like SIEM and NTA?

UEBA enhances the capabilities of other cybersecurity solutions like SIEM (Security Information and Event Management) and NTA (Network Traffic Analysis) by providing advanced threat detection and behavior analysis. While SIEM focuses on event monitoring and reporting, and NTA on network traffic analysis, UEBA offers deeper insights into user and entity behavior, helping organizations identify and respond to threats more effectively.

What are the benefits of integrating UEBA into an organization’s cybersecurity strategy?

Integrating UEBA enhances an organization’s ability to detect and respond to cybersecurity threats by providing comprehensive monitoring of user and entity behavior. This proactive approach helps organizations identify potential threats early and take appropriate action to mitigate risks, ultimately strengthening their overall cybersecurity posture.

How does UEBA help organizations comply with security regulations?

UEBA assists organizations in complying with security regulations by detecting behavioral anomalies and ensuring adherence to security policies and standards. By monitoring user and entity behavior, UEBA helps organizations identify and address compliance issues promptly, reducing the risk of fines or legal proceedings associated with security breaches.

Is UEBA suitable for organizations of all sizes?

While UEBA offers significant benefits for organizations of all sizes, its implementation may vary depending on the organization’s specific cybersecurity needs and resources. Larger organizations with complex security requirements may benefit more from UEBA’s advanced threat detection capabilities, while smaller organizations may find alternative solutions more suitable based on their budget and infrastructure.

How can organizations evaluate the effectiveness of a UEBA solution?

Organizations can evaluate the effectiveness of a UEBA solution by assessing its ability to accurately detect and respond to cybersecurity threats, its ease of deployment and integration with existing infrastructure, and its impact on reducing cybersecurity risks and enhancing overall security posture. Regular monitoring and assessment of key performance indicators can help organizations measure the success of their UEBA implementation.

Conclusion

UEBA is a pivotal advancement in cybersecurity, offering proactive threat detection by monitoring user and nonhuman behavior. With algorithms and machine learning, it helps mitigate risks and safeguard digital assets. By including entities like devices and applications, it provides a holistic view of threats. UEBA is crucial for organizations of all sizes to enhance security, comply with regulations, and combat evolving cyber threats effectively. Integrating UEBA into cybersecurity strategies enables organizations to stay ahead of emerging threats and maintain resilient defenses.