What are User Behavior Analytics and How Can It Protect Against Insider Threats

As a business owner, you know that your company assets contain valuable information. That’s why you work hard to keep your critical assets secure and your company production safe at every turn. 

However, the unfortunate reality is that any business could fall victim to a cyberattack or a malicious attack at any time. Data breaches in the form of an insider attack or malicious external attack are prevalent and could strike your business at any moment. 

One way to protect against cybercriminals is by implementing User Behavior Analytics (UBA) or User and Entity Behavior Analytics (UEBA). UBAs and UEBAs are a type of technology that can track behaviors on a given network and report when behaviors seem to stray from outside the norm. UBA tools can support insider threat detection and help prevent a malicious attack. 

What is User Behavior Analytics?

User Behavior Analytics is a cybersecurity process and technology that helps a company protect against an insider threat, targeted attack, and financial fraud. UBA software is commonly used in employee monitoring because it can track common behaviors and alert a security analyst or security team and management when employee behaviors have deviated from the norm. 

This type of technology is usually powered by machine-learning solutions since the algorithm can look into normal behaviors, report trends, and then notice when behaviors have deviated from those trends. 

UBA, sometimes also referred to as user and entity behavior analytics (UEBA) if the system can monitor entity behavior, involves tracking, collecting, and the assessment of behavior data collected by a monitoring system. A UBA or UEBA system uses historical data logs as a way to analyze current behaviors from past behaviors, decide what common behaviors should be expected, and identify what could be considered abnormal behavior. UBA monitors behavior from an individualized perspective while UEBA monitors behavior from the entity perspective.

A user behavior analytics tool might track authentication logs, network logs, traffic patterns, and more. This information is usually stored in security information and event management (SIEM) systems and gives a cybersecurity team actionable insights when a red flag for abnormal or malicious behavior is detected. 

The UBA system does not actually do anything to stop a malicious insider, but simply provides valuable information for the cybersecurity team. The UBA can be configured to “watch” those users who are contributing to anomalous behavior, allowing for closer monitoring. 

Ways your business can use User Behavior Analytics

Early versions of behavioral analytics appeared in the 2000s as a way for marketing teams to analyze and then predict customer buying patterns.

Now, UBA systems can be integrated into SIEM systems for advanced profiling and exception monitoring capabilities that are more advanced than a standard SIEM system. UBA and UEBA software is also compatible with employee monitoring systems and are often incorporated into the employee monitoring software itself. 

The two main functions of UBAs are:

  • To determine the baseline normal behavior and activities within an organization and its users
  • To identify anomalous activity within that organization

UBAs use big data and machine learning to detect behavior deviations, so a company will be notified of an insider incident in almost real-time. If a security event is detected, the team can work up an appropriate insider threat solution and incident response to mitigate the threat. Or, the security team can choose to bring in an advanced assessment team to monitor the behavior and stop a major cyber attack before it happens. 

Since UBAs can be run on a large scale and across multiple users in a company, security analytics are accurate at measuring cybersecurity threats such as data exfiltration, compromised credential information, compromised endpoints, potential insider threats with malicious intent, and malware. 

How User Behavior Analytics works

User Behavior Analytics is essentially an algorithm that collects, analyses, and assesses historical data, user activity, user location, and security alerts to protect against potential threats. 

UBAs do behavior monitoring by looking at individual user roles, user titles, access to given accounts, accounts and permissions, user activity, past user infringement, and firewall detectors. Data is collected and assessed from historical logs but the system also monitors current activity, resources used in real-time, duration of sessions on accounts and within folders, connectivity, access points, and peer group activity. 

It then uses the interpretation of this data to compare to identify potential “anomalous behavior”. When anomalous behavior is detected, the system will automatically update itself so that it monitors that behavior. 

A UBA solution will not report all anomalous behavior as being risky. If it did, it would be reporting common changes as risky and alerting your team needlessly, creating a “boy who cried wolf” scenario. 

Instead, UBAs can monitor the potential impact of behavior and score it based on the behavior’s impact. For example, if a file containing sensitive data or critical assets is being accessed by someone without the security credentials, then the system might flag that behavior as anomalous, as it could be a potential security incident. The anomalous behavior related to that access is marked as having a higher impact. 

With these security tools, a security professional can prioritize or de-escalate a security threat without having to wade through loads of potentially non-risky behavior. The UBA system teaches itself that certain behaviors are normal (or should only be monitored) and therefore reduces the chance of a false positive. UBAs and UEBA’s should be implemented into a cybersecurity and insider threat program.

How User Behavior Analytics can reduce insider threats

Since UBAs give cybersecurity teams clearer insight into insider risk intelligence, they can focus on minimizing the insider threats that they have been alerted to. The team can also monitor the UBA data in real-time to assess whether too many basic movements within the network are being flagged and taking up their time and attention. 

If an employee accessed a file or network that they aren’t supposed to, this can show the cybersecurity team that there is a loophole somewhere. It might also indicate that you have a negligent insider, compromised credentials, or malicious activity.  

One of the most important aspects of UBAs is that they are not alerting the cybersecurity team to too many false positives. Instead of being alerted every time a file is moved within a folder, the system can be configured to expect certain changes. 

Additionally, UBA data can be used to generate a user or employee report so that other members of the company can be informed as to the employees’ company profile activity. If the employee has more alerts than some of the other employees, that could be an indicator that they regularly perform risky behavior and need training. 

UBAs can move beyond collecting user data and collect activity from devices, applications, and services to create a more comprehensive profile of behavior data. 

With this level of entity behavior analytics, cybersecurity teams are able to combine behavior data of individuals with behavior data from entities so the technology can look past insider threats and look at those anomalies that aren’t known to be threats but could be potential insider threats. 

Using User Behavior Analytics 

It is becoming necessary that every business invests in UBAs and UEBAs so that the chance of an insider threat is minimized and that your assets are protected. 

Since insider threats are costly, hard to detect, and the cause for around 50% of all data breaches, it is important that your company protect yourself with a UBA integrated into your SIEM system. 

September 14th, 2020