What is UBA and UEBA Software: Introduction to Behavior Analytics

Having a solid data security in place has never been more important for businesses, as advances in technology continue to introduce new opportunities for security threats to emerge. Companies often need to be extremely vigilant in building their internal and external security defenses.

In some cases, internal threats can be even more of a risk than external threats because they are usually harder to detect and hidden from view. With the growing popularity of remote work and the widespread use of mobile devices in everyday work transactions, relying solely on employee monitoring software might not be sufficient in the long run. Seeing how data security protocols are becoming weaker, risks of intentional or accidental leaks of sensitive information are becoming more and more probable.

To alleviate the threats of insider leaks of valuable company data and in order to improve their data security, companies need to combine traditional data loss prevention tools with user behavior analytics. A more holistic approach to preventing data breaches is essential to ensure the safety and security of valuable and sensitive information.

This is where user behavior analytics solutions come into play, which help managers see all the activities of their employees in order to create a baseline of their typical work behavior patterns. Once these baselines are developed for each user and their real-time activity is monitored, it becomes easier to spot any irregularities. In case of any suspicious behavior, managers can then identify potential security threats, unauthorized access attempts, or even full-blown data breaches, thus strengthening their internal company security protocols.

What Is User Behavior Analytics?

User Behavior Analytics (UBA) is a technology that enables companies to detect potential insider threats based on analyzing user behavior and identifying unusual or suspicious activities (anomalies) that may indicate the presence of a threat. Behavior is understood as the actions and communications of workstation users (personnel) with devices, applications, websites, and other objects in an information system. Both standalone software solutions and modules that are integrated into various security systems work on the basis of this technology.

The main task of UBA is the timely detection of targeted attacks and insider threats. UBA solutions process a large amount of data from various sources. The indicators collected as a result of monitoring communications and actions of employees form the basis for user profiling (including suspicious employees), which implies their categorization into different groups depending on behavioral patterns, based on the analysis of their daily working behavior and comparing it with average (normal) indicators. If an employee's behavior is out of the norm, they are placed in a risk group and the information security officer is notified.

How Does User Behavior Analytics Work?

Analytics is an important element of UBA. UBA (User Behavior Analytics) techniques, which are based on machine learning as well as probability, graph, random process and mathematical statistics theories, are used to ensure the security of computer systems by detecting unusual or potentially malicious user behavior.

To analyze employee activity, UBA software needs various types of data, including access, accounts and permissions; user activity and geographical location, for a certain time period – an archive of several months usually suffices. The source of such data can be a separate archive or a DLP solution. The analysis also takes into consideration factors such as resources used, the duration of sessions, and connectivity to compare anomalous behavior to. 

The UBA solution constructs a behavioral profile by collecting and processing data on employee activity. For example, in the course of its work, the engine studies the total number of messages, the ratio of incoming and outgoing messages, email traffic that goes outside the company, the time of message sending, the circle of communication (external, internal, unknown contacts) and recipients.

Then, based on information from communication history, machine learning algorithms allow the UBA engine to determine typical user behavior and identify deviations from it (anomalies) that may indicate a security threat. An increase in communication activity, requests for various documents from colleagues, or a large number of emails with attached files can all indicate a potential information leak. Moreover, behavioral analysis can also be used to detect economic crimes, such as violations related to tender procedures.

The combination of behavioral indicators (including anomalies) and the nature of recorded security events allows UBA solutions to categorize users based on their behavior patterns (certain characteristics typical for company employees), such as anomalous behavior, frequent communication with unknown third-party contacts, overall lack of activity, etc.

Behaviors that UBA engines monitor are generally those associated with specific attacks or other security events. Monitored behaviors might include the following:

• brute-force attacks;
• improper data access;
• data loss;
• questionable or unauthorized user activity.

Overall, UBA analysis methods provide an effective way to ensure data security by detecting unusual or potentially malicious user behavior.

What is the Meaning of User Behavior Analytics?

Successful mitigation and prevention of today's rapidly evolving cyber threats requires robust data security management, and user behavior analytics plays an important role in protecting sensitive information. By identifying anomalous user behavior, businesses can more effectively address any potential threats and implement the improvements needed to create sustainable cyber security protocols. 

What’s more, it costs companies much less to prevent data breaches than to remediate them. After all, they can lead to not only valuable data leaks, but also to reputational damage, loss of customer trust, and loss of competitive advantage.

What Are the Limitations of User Behavior Analytics?

This class of solutions has its own specific limitations, and it would be beneficial for users to be aware of the following characteristics.

1. If security officers want accurate monitoring and analysis of employee behavior, they must provide the UBA solution they are using with sufficient data. This data must be representative of a fairly long period of time and should come from at least a few sources.

   This process can be accelerated by using past data that can be provided to the UBA solution for processing. This option is possible if the company keeps retrospective data on the activity of its employees that is sufficient for UBA analysis.

2. Secondly, UBA solutions have certain specific features related to the very approach they are based on. The behavior of some users might exhibit fluctuations according to a number of indicators during certain periods. This is common for employees in senior management positions. For such users, it is difficult to determine stable behavioral patterns using UBA tools in the first place. In such cases, security specialists need to use additional means of analyzing the data with which the employee works in order to accurately detect violations.

   On top of that, the behavior of certain malicious users may be anomalous from the very beginning of implementing the UBA solution. If an employee commits violations on a regular basis, the UBA engine will perceive this negative behavior as typical and thus "normal" from the very beginning of the analysis. In this case, as with the fluctuating employee behavior described above, analysis of the details can help identify violations.

3. Not all UBA solutions come with the capacity to dynamically adjust to changing user behavior. Yet people do change. The most obvious reasons for changes in employee behavior are reorganization of business processes, shifts in job responsibilities or positions in the organization, as well as personal problems.

   UBA solutions must be flexible enough to adapt to such changes. Thus systems that do not have built-in adaptability require regular maintenance. Updating data regarding the typical behavior of employees in such a case becomes a mandatory periodic procedure that requires the involvement of analysts.

4. When implementing UBA solutions, a certain degree of maturity of security officers as well as their willingness to utilize UBA in their work on a regular basis plays an important role. UBA solutions could fail to work successfully if security officers are simply not ready to independently analyze the results provided by the software, look for violators, and evaluate the effectiveness of the proposed models manually.

What Are the Benefits of Using UBA tools?

Advanced UBA analytics are used to prevent internal incidents related to cybersecurity, as well as to investigate and reconstruct the course of events. The implementation of behavioral analytics technologies allows managers to address risks proactively. For example, UBA tools can help detect malicious users before any data leaks occur, reveal employees' affiliations and personal connections, as well as detect workers who plan to take work-related documents prior to leaving the company or use their position to earn extra money.

UBA solutions address the following challenges:

1. Identifying and preventing internal violations related to data leaks

   Human error remains a major threat to any company. UBA automatically analyzes employee behavior patterns. Using mathematical algorithms and statistical analysis, the engine identifies anomalies in these patterns that could pose a possible threat. Instead of collecting and analyzing information about the devices being used and events that occur, UBA tools typically focus on information about the individuals who use the devices. For example, if a user starts uploading sensitive information to cloud storage and that has never been observed for them before, UBA will identify that type of activity as abnormal for this specific individual and bring it to the attention of the data security officer.

2. Profiling user activity

   UBA engine performs an analysis of employee behavior and builds a profile of each user's behavior based on that information. Usually, their normal behavioral properties are not of interest to security professionals in and of themselves. They do, however, pay attention to them when these behaviors start to deviate from the norm. The nature of the behaviors most often correlates with the type of work the employee is doing. A significant discrepancy between perceived and actual behavior may indicate a threat.

3. Monitoring and detecting behavioral deviations, large-scale dangerous trends, and previously unknown risks

   Tracking dynamic indicators of normal and abnormal user behavior makes it possible to identify trends of various kinds, including negative and dangerous ones. This allows organizations to respond to incidents, identify malicious insiders, and proactively take the necessary steps to prevent data security threats.

4. Investigating incidents

   UBA also helps companies to investigate incidents related to insider threats. This can be done by looking for correlations between cyber security events and behavioral anomalies.

What Are the Best UBA Tools in 2024?

Kickidler DLP – for collecting, analyzing, and acting on user behavior data

Kickidler DLP module is one-of-a-kind software with human-focused behavioral analysis features that enable businesses of all sizes to discover and classify sensitive data across their network, cloud, email, web as well as monitor and protect sensitive information from exposure by employees and third parties.

The large data sets that are collected by the solution are given a new operational meaning by predictive analytics and machine learning technologies, the benefits of which include reducing manual labor, helping to proactively avoid potential insider threats, and taking data protection to a whole new level.

Key features:

• Insider Threat Prevention
• Data Misconduct Detection
• UBA functionality: smart keyboard behavior analysis, smart audio conversation analysis, web search monitoring, CPU/GPU usage monitoring, monitoring employee contact lists
• Continuous Data Monitoring
• Employee Monitoring

Pricing:

Kickidler offers a free version that enables monitoring of a single user. Its Time Tracking version costs $4.9 per month for each license (when billed monthly). Its Employee Monitoring version costs $9.99 per user per month for a single license (when billed monthly). Its Data Loss Prevention version costs $19.99 per user per month for a single license (when billed monthly) and offers a variety of insider threat prevention, data misconduct detection, and continuous data monitoring features.

Hotjar – for heatmap data analysis

Hotjar is a user behavior analytics tool that helps businesses analyze website performance and user behavior across mobile and web. Hotjar offers an intuitive, visual way to discover, consolidate, and communicate user needs with minimum fuss.

Hotjar has session recording, funnel analysis, and user segmentation features. But it also takes heatmaps a step further. Not only does the platform generate heatmaps that show scrolls and clicks, but it also lets managers extract and save insights from the heatmaps to get a better understanding of what’s happening in the teams.

Relevant features:

• Heatmaps
• Session Recordings
• Feedback
• Surveys
• User interviews
• Integrations

Pricing:

Hotjar offers a free plan and three paid plans, the prices for which vary based on the number of required daily sessions.

Its Basic plan is free and includes up to 35 daily sessions. Its Plus plan costs €39 per month (when billed monthly) and includes up to 100 daily sessions. Its Business plan costs €99 per month (when billed monthly) and includes 500 daily sessions. Its most comprehensive Scale plan costs €213 per month (when billed monthly) and includes everything in Business, as well as full access to every feature.

Google Analytics 360 – for in-depth reporting

Google Analytics 360 is an enterprise-level analytics platform with in-depth performance indicators, such as ROI analysis reports. Its primary function is to provide insights into customer behavior interactions with websites and apps to identify effective content. The platform’s centralized dashboard displays overviews and reports. The engine connects with other applications, like CRMs and POS systems, to provide detailed overviews of customer behaviors.

Google Analytics 360 uses machine learning to discover customer trends and patterns in the data. It identifies users with high revenue potential and identifies content converting the most customers. 

Relevant features:

• Automation and analytics
• Reporting
• Advertising Workspace
• Explorations
• Data Collection and Management
• Advanced-Data Governance

Pricing:

Google Analytics 360 is a free tool.

CleverTap – for mobile-first products

CleverTap is a user behavior analytics and automation tool that helps businesses retain their most valuable users and grow customer lifetime value.

CleverTap combines audience analytics, omni-channel engagement, and product A/B testing to help businesses deliver a truly personalized customer experience.

Relevant features:

• Automated User Segmentation
• Omni-channel Engagement
• Journey Orchestration
• Campaign Optimization
• Lifecycle Optimization

Pricing:

CleverTap offers a 30-day free trial. It also has a fixed-rate Essentials pricing plan that starts at $75 per month. Details on their Advanced and Cutting Edge pricing plans are provided on demand.

Conclusion

In recent years, solutions designed to analyze user behavior have been appearing in the global security market and are becoming more and more in demand. In particular, UBA systems are actively used by industries that are focused on personnel monitoring, behavioral analysis, and discovery of significant deviations in the employee behavior pattern in order to detect and avoid data security incidents, identify threats to business, prevent violations, and manage risks. In other words, it is mostly used those areas for which the human factor is critical. After all, according to the modern approach to data security, it is the human being who is the main source of security breaches, threats, and risks. Behavioral analysis systems are also useful for such areas of activity as human resources management, finance, strategic management, and managerial decision-making.

These systems are beneficial due to the fact that they utilize the most advanced methods of analysis, evolving through experience, discarding outdated techniques and adding the most effective ones to their arsenal.

The spectrum of UBA application in the data protection area is quite wide: it includes detection of malicious insider threats, prevention of valuable information leaks, detection of compromised accounts, prevention of unauthorized access to data, and mitigation of cyberattacks.

The global market offers a vast variety of UBA solutions, both stand-alone and integrated into adjacent security products (typically, it's SIEM, DLP, IAM, etc.).

The greatest prospects can be seen for those solutions that not only fulfill the basic tasks of UBA products, but also facilitate the development of new capabilities. Such assisting things include clarification of operating principles, availability of application methods, positive experience of solution implementation, ready-to-use scenarios, and clear step-by-step instructions for mastering the tool. The shorter period of full activation at a new deployment and the ability to use retrospective data for analysis when deployed at existing client sites are also undoubted advantages.