Best User Behavior Analytics (UEBA) Solutions

While they may seem synonymous, UBA and UEBA are distinctly different. While UBA can detect and track suspicious activities and behaviors, UEBA is able to detect abnormalities that are more complex across multiple users, devices, and IP addresses. Unlike UBA, UEBA tracks user activity and other entities. These entities may or may not include managed and unmanaged endpoints, networks, applications, and external threats.

1. Use cases are one of the three pillars that provide insight into the abnormal behavior of users and entities within a corporate network by monitoring, detecting, and making alerts of anomalies.
2. Data sources are used to collect various types of data from a repository. The repositories often include data from a data lake or warehouse or an external system like SIEM (security information and event management).
3. Analytics are used to detect abnormal behavior, either through supervised or unsupervised machine learning or other methods like rule-based analytics, statistical modeling, or threat signatures. Data analysis allows baseline profiles and patterns to be created so that anomalies can be detected by comparing those profiles to user or device behaviors.

UBA and SIEM (security and information event management) are closely related. UBA tools work in conjunction with SIEM solutions to reveal anomalies in behavioral patterns within a network. To perform analysis, UEBA relies on security data which is collected and stored by a SIEM. UBA works in real time to uncover unknown threats and anomalies, whereas SIEM uses point-in-time analysis, which means that it can only process a limited number of events in a particular time frame. By combining UBA with a SIEM solution, human and machine behavior can both be spotlighted, providing organizations with the benefits of advanced threat detection that traditional security tools often miss.

User behavior can be defined as how users interact with a website. Typically, this can refer to any action a user takes, such as the amount of time they spend on a specific page, how many pages they visit, how long they remain on the clicked pages, which links they click on, how they scroll, when and where they leave the website from, and much more. Tracking user activity can be especially helpful when related to threats or cyberattacks. Detecting potential risks or threats before they escalate can save organizations from experiencing damage to their systems, and can save lots of money and time.

Behavior analytics tools are tools used by an organization for analytics, statistics, data protection, or breach prevention. With the hacking incidents increasing more and more frequently, using behavioral analytic tools has become a crucial element for all businesses. The primary goal of behavior analytics tools is to track a user's behavior and data usage, as well as network events and typical behavior patterns to easily identify potential threats based on detected anomalies.

UEBA solutions work by analyzing the normal behavior of users and entities within the network to establish a baseline. Machine learning algorithms then detect deviations from this baseline, flagging behaviors indicative of potential insider threats. You can understand what constitutes normal activity for each user and entity, allowing for precise detection of anomalies that could suggest malicious intent or compromised accounts.

Machine learning is central to UEBA as it powers the continuous analysis and learning from user activities. It helps by self-adjusting baselines and improving detection accuracy over time. By learning from past incidents, machine learning enables the system to refine its anomaly detection processes, offering you more reliable alerts and insights into potential security breaches.

Implementing UEBA solutions significantly enhances your organization's security posture by providing real-time detection and response capabilities against both insider and external threats. By integrating UEBA, you receive insights into user activities and potential vulnerabilities, enabling proactive defense measures and reducing response times to incidents.

Deploying UEBA solutions involves challenges such as integrating with existing systems and managing the volume of data generated. It requires investment in infrastructure capable of handling extensive data analysis. You'll need to ensure data privacy and compliance when monitoring user activities, which can require additional resources and strategic planning.

UEBA solutions can complement your existing Security Information and Event Management (SIEM) systems by enhancing threat detection capabilities. While SIEM systems aggregate and analyze logs from across the network, UEBA adds a behavioral layer to this analysis, identifying anomalies that SIEM might miss. The integration allows for more comprehensive threat intelligence and streamlined incident response.