Cyberattacks are increasingly sophisticated, making traditional digital security tools insufficient to protect organizations from malicious actors.
In 2015, Gartner defined a category of solutions called User and Entity Behavior Analytics (UEBA).
Its big advantage is monitoring suspicious behaviors of human users and devices in corporate networks through algorithms and machine learning, determining if there are threats and issuing alerts to security teams.
In this article, we explain more about this subject, which is extremely important for the security of your company. To facilitate your reading, we divided our text into the following topics:
- What Is User and Entity Behavior Analytics?
- How Does UEBA Work?
- What Are Its Three Pillars?
- What Are the Benefits of UEBA?
- Disadvantages of User and Entity Behavior Analytics
- Best Practices for User and Entity Behavior Analytics
- What Is the Difference Between SIEM and UEBA?
- UEBA X NTA
- What Is UBA and What Is It For?
- What Is the Difference Between UBA and UEBA?
- senhasegura UEBA Solution
What Is User and Entity Behavior Analytics?
User and Entity Behavior Analytics (UEBA) is a digital security feature that uses algorithms and machine learning to identify abnormal behaviors in users, routers, servers, and endpoints of a network.
In practice, this technology allows alerting IT administrators about anomalies and automatically disconnecting users with unusual behavior from the network, as it monitors human and machine behavior.
With this, it helps detect people and equipment that could compromise an organization’s system, strengthening its digital security and sovereignty.
How Does UEBA Work?
To ensure the effectiveness of User and Entity Behavior Analytics, it is necessary to implement this feature in the organization’s infrastructure, which can be targeted by malicious attackers.
Moreover, many corporations ask their employees to install this solution on their home routers to avoid risks. This is because the professional may have to access the corporate network using their own router, generating security vulnerabilities.
It is very simple to understand how UEBA works. Let’s imagine an unauthorized user steals an employee’s credentials and accesses the network. This does not make them capable of imitating this employee’s usual behavior.
Therefore, UEBA issues alerts, which reveal suspicious behavior to IT administrators. A UEBA solution has three essential elements. They are analytics, integration, and presentation.
Analytics collects and organizes data about the behavior of human users and entities to determine what should be considered normal. Through this system, profiles are created of how each user behaves when accessing the network. Thus, one can develop models that allow the identification of suspicious behavior.
With the growth and evolution of corporations, it becomes necessary to integrate UEBA into other security systems. Through proper integration, UEBA solutions compare information collected from different sources, which optimizes the system.
Finally, the presentation involves how User and Entity Behavior Analytics responds to abnormal behaviors. It depends on what is defined by the company.
Some UEBA systems are configured to simply create an alert, suggesting an investigation for IT administrators. Others are configured to perform additional actions, such as disconnecting an employee with abnormal behavior.
What Are Its Three Pillars?
According to Gartner, a UEBA solution has three pillars:
- Use cases;
- Data sources; and
- Analytical methods.
Use cases refer to the behavior of human or machine users reported by User and Entity Behavior Analytics, which monitors, identifies, and alerts about anomalies. Unlike systems that perform specialized analysis, UEBA technology needs to be relevant to different use cases.
When we talk about data sources, we refer to repositories of information that feed into UEBA, since User and Entity Behavior Analytics does not collect data directly from IT environments.
Analytical methods are what enable UEBA to identify abnormal behavior. They include threat signatures, statistical models, rules, and machine learning.
What Are the Benefits of UEBA?
Traditional security solutions have proven ineffective at protecting corporations from sophisticated cyberattacks, which has boosted the rise of User and Entity Behavior Analytics, as it allows one to identify even the smallest of unusual behaviors.
Its main benefits include:
Broad Approach to Cyberattacks
In addition to monitoring the behavior of human users, UEBA monitors devices such as endpoints, servers, and routers, which are often targeted by malicious attackers.
Thus, User and Entity Behavior Analytics detects a wide variety of cyberattacks, including insider threats, compromised accounts, brute force attacks, and DDoS.
With the use of artificial intelligence and machine learning, UEBA solutions can replace the workforce of IT employees, which represents a benefit for corporations and security teams.
Nevertheless, User and Entity Behavior Analytics does not generate a drastic reduction in IT staff, especially in larger organizations, due to the complexity of security requirements, which require skilled people to configure systems and guide employees.
These professionals may also be responsible for investigating abnormal behaviors if the company decides to investigate them before taking measures.
In addition, IT analysts can develop other projects, working strategically for business growth.
With the reduction of the IT team, an organization consequently reduces costs. Also, by detecting abnormal behavior and preventing cyberattacks, companies prevent losses by stopping activities.
They also avoid having their customers’ and employees’ data exposed, which could result in fines due to data protection laws.
With professionals connected to corporate networks, including in a home environment, vulnerabilities caused by cyber threats increase gradually, making protection solutions in silos insufficient.
For IT teams, it is impossible to manually monitor all devices in use. Hence the perks of UEBA solutions.
It is worth mentioning that UEBA resources are not limited to ensuring information security. They also enable compliance with security standards for regulated industries, avoiding problems that could lead to lawsuits and fines for companies, as previously mentioned.
Disadvantages of User and Entity Behavior Analytics
The UEBA solutions also have some negative aspects. The first one is its high price, which can make this technology inaccessible to small and medium-sized businesses.
Another disadvantage of User and Entity Behavior Analytics is the slow deployment. Although many vendors claim this system can be deployed in a short time, Gartner customers say that in simple use cases, it can take three to six months, and in complex situations, it can take up to 18 months.
In addition, the view UEBA offers over network behaviors is restricted as its logs are enabled on a small part of a corporation’s network.
It is also important to keep in mind UEBA needs third-party logs to work. Failures in the generation of these logs impact its function.
Best Practices for User and Entity Behavior Analytics
User and Entity Behavior Analytics is designed to identify abnormal behaviors of humans and machines.
However, this solution should not be used in isolation but associated with other monitoring systems, in order to improve the digital security of an organization. Other best practices for companies using UEBA resources are:
- Avoiding false alerts and overloading of generated data, taking advantage of big data resources, and using machine learning and statistical analysis;
- Creating security policies taking into account insider and external threats;
Ensuring that only information security professionals receive alerts from UEBA; and
- Not underestimating the risks posed by unprivileged user accounts, as hackers can increase privileges to gain access to sensitive systems.
What Is the Difference Between SIEM and UEBA?
Like UEBA, Security Information and Event Management (SIEM) features tools that make it possible to improve information security through normal patterns and suspicious behaviors.
The notable difference is that User and Entity Behavior Analytics uses data from human and machine user behavior to define what is normal.
Because SIEM is rule-based, malicious actors can circumvent these guidelines to attack a corporation. Also, SIEM detects threats that happen in real-time, but it is inefficient to prevent sophisticated attacks performed over months or years.
UEBA, on the other hand, is not based on rules, but on risk-scoring techniques and algorithms, which make it possible to detect abnormal behavior over a much longer period.
UEBA X NTA
Like UEBA, Network Traffic Analysis (NTA) solutions are based on machine learning, advanced analytics, and security rules, and monitor user behavior on corporate networks. Moreover, it detects suspicious actions and threats.
However, this technology has other advantages. One is to allow companies to visualize everything that happens on their network, including in the context of a cyberattack. NTA also makes it possible to create network profiles and devices, with easy deployment.
We emphasize these two solutions should be used in a complementary way, since NTA alone does not track local events, nor detect advanced security problems.
What Is UBA and What Is It For?
User Behavior Analytics (UBA) is a technology that allows one to identify unusual or abnormal behaviors, detect intrusions, and minimize their consequences.
Through UBA solutions, one can discover an invasion promoted by cybercriminals or find out if an employee is misusing the data to which they have access.
The focus of User Behavior Analytics is on user analytics, their accounts, and identity, not machine behavior.
What Is the Difference Between UBA and UEBA?
The difference between UBA and UEBA is that, in the first case, we refer to a solution that monitors human users to detect any anomalies in their behavior.
The extra “e” in UEBA extends monitoring to machine entities such as routers, servers, endpoints, and devices in general.
The acronym was updated in 2017 by Gartner to show that in addition to tracking human users, it is essential to identify threats related to devices and applications.
senhasegura UEBA Solution
senhasegura has a UEBA solution embedded in its PAM security platform, which allows one to monitor the behavior of human and machine users automatically.
This technology features a self-learning mechanism to identify and respond to changes in users’ behavior patterns and access profiles.
Some of the main characteristics are:
- Analysis of user session based on behavioral history;
- Identification of accesses and check of suspects by a series of criteria;
- Identification of unusual behavior with abnormality alerts for SIEM/SYSLOG;
- Detailed dashboards with a visual representation of incidents and threats, which allow a security team to act quickly;
- Algorithms are continuously adjusted to user behavior.
Its benefits include:
- Restriction of privilege abuse;
- Fast detection of attacks and compromised accounts;
- Control over the user’s administrative actions;
- Automatic response to suspected credential theft.