Top 8 User Behavior Analytics - UEBA Tools
CynetOne Identity SafeguardSecuronix Security AnalyticsRapid7 InsightIDRExabeam Fusion SIEMSplunk User Behavior AnalyticsManageEngine Log360IBM QRadar User Behavior Analytics
We are protecting all our workstations.
It's transparent, so it's not something where every user has to press a button to download or do the thing. It is centralized, in fact. Personally, I use Malwarebytes and other tools, which are fine for home use. Cynet is also relatively silent in terms of operation, except when it's required to act.
Safeguard can define and update processes and procedures into the security framework of a company, including mobile. It allows us to change the policies and configurations on a mass scale in regards to security.
The solution is stable and scalable.
There aren't any positive aspects of the solution. It was a complete failure. There are no redeeming features.
Rapid7 InsightIDR integrates well with other solutions. It's also easy to configure because Rapid7 InsightIDR has a lot of instructions posted on their website that customers can follow if they need to get the source log.
It's a very user-friendly product and it's a very comprehensive technology.
Exabeam's easy to use.
The solution appears to be stable, although we haven't used it heavily.
This is a good security product.
It is nice to be able to monitor and to have notifications.
It basically helps us. We have to stay in compliance with certain issues with some of our customers. We have to have these types of tools in place for protecting our network and our data. We're in the aerospace industry, so we have a lot of defense contracts. So, all those guys will make sure that we're protecting their information, and it does a good job in that aspect.
Integration is very easy and the reporting is good.
It provides many options for searching. I can see devices from different vendors, like Cisco, in one interface, which is good for me.
What is user entity behavior analytics?
User entity behavior analytics, otherwise referred to as UEBA, slowly emerged to replace UBA, offering more powerful solutions. As the threat landscape grew, “entities” were added to UBA to monitor malicious behavior beyond the user level. While UBA can detect human behavior within a network, UEBA can model behaviors of humans as well as the machines within networks, including devices, in addition to applications as well as networks, providing complete visibility. When behavioral abnormalities are associated with an entity (i.e. a particular IP address), attacks hardly go unnoticed. By using a baseline of normal user and machine behaviors, UEBA can recognize when a machine is compromised, and thus minimize the amount of damage that can be done.
What is the difference between UBA and UEBA?
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.
What are the three pillars of UEBA?
- 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.
- 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).
- 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.
What is UBA in SIEM?
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.
How do you define user behavior?
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.
What are behavioral analytics tools?
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.
Benefits of User Behavior Analytics Tools
There are many benefits of using behavior analytics tools. These include:
- Automatic detection: Internal and external cyberattacks (whether they be compromised accounts, data breaches, or the creation of new users) are automatically identified.
- Decreased number of security analysts: With automated systems in place, fewer security analysts are needed.
- Reduces cybersecurity budget: With less security analyst staff to employ, organizations can save on cybersecurity costs.
- Business process optimization: UBA tools allow organizations to have complete transparency. Because every action is documented, businesses can analyze which processes are working and which ones are costing too much money, etc. With this information at hand, businesses can make more informed decisions and test new methods to optimize and scale business processes.
- Additional visibility: Anomalous or unexpected behaviors that violate company policies can also be monitored. Organizations can receive tactical notifications when employees take liberties.
User Behavior Analytics Tools Features
Below is a list of some key features to consider when choosing a UBA tool:
- Machine learning: Monitor both individual user and group activities by choosing a UBA tool that incorporates machine learning.
- Easy-to-use dashboard: When a dashboard is intuitive and easy to understand, it provides instant visibility of suspicious activity or attacks.
- Data movement: It is useful when you are able to track your data flow movement, both online and offline.
- AI-based: With the addition of an artificial intelligence-based feature, organizations can identify real risks and threats.
- Dynamic visualization: This feature allows companies to easily gain insight into historical activities.
- Notifications: Detailed alert notifications can be set up to give complete insight into an incident.