Defining and Understanding User and Entity Behavior Analytics (UEBA)

Defining UEBA

This is basically a cybersecurity solution that can recognize and essentially remember normal user behavior. As such, it can identify weird or anomalous instances whenever a user or an entity deviates from their regular “pattern.” A good example of this is if a user normally downloads 10MB worth of data in a da, but suddenly starts to download 100GB, the UEBA would detect this as anomalous and flag it.

A great feature of UEBA is that it uses a combination of machine learning, statistical analysis, and complex algorithms in order to detect deviations in patterns that can lead to harmful effects for the entire system. The UEBA can essentially aggregate the data that you have.

The main difference of UEBA is that it does not track events or monitor devices; instead, it tracks the actions of all the organization’s users and its entities. It focuses more on insider threats, which can include rogue employees or those who have been compromised by outside machinations.

Benefits of UEBA

Hackers and malicious attackers are evolving to the point that conventional security tools are fast becoming obsolete. Firewalls, gateways, and intrusion prevention applications can be bypassed now, which is especially true with bigger corporations, since their IT is more complex to maintain and manage.

Detection is now incredibly important, more so than ever, because it is just a matter of time for hackers to figure out your defenses and get into the network. It is up to other systems, such as UEBA, to detect anomalous activities for immediate response and potential threat prevention.

How UEBA Works

The concept of UEBA is quite simple. Hackers can steal usernames and passwords, but it would be difficult for them to mimic an employee’s habits or normal behavior when accessing the company’s network, especially since their intent is to steal rather than to work.

A relatable analogy here is if a thief is able to steal your credit card. That thief would then go on a shopping spree, using your card in retail stores that you do not normally visit. This would trigger the bank’s fraud detection policies.

Because of this, UEBA has proven to be an important part of any organization’s IT security.

It can detect insider threats, such as an employee or group of employees who’ve decided to go rogue against the company by stealing data. This can be detected by UEBA.

It can detect compromised accounts like in the above example. A hacker may obtain the username and password of an employee and start stealing information. This anomalous behavior can be detected by UEBA.

A brute-force attack is a common hacker tool that can be hindered or otherwise prevented by UEBA.

It can detect changes in user permissions or the creation of super admins to flag these, especially if they are deemed unnecessary by the system.

UEBA can prevent unauthorized access of sensitive and protected data, limiting access to only those who actually need said data.

Best Practices of UEBA

UEBA was established due to the malicious behavior of users and other entities. It is not meant to replace other monitoring systems but to complement them instead, which enhances your organization’s overall security.

It is a great idea to harness Big Data, statistical analysis, and mechanical learning in order to prevent a huge increase in useless alerts due to the large amount of data generated.

UEBA essentially helps you take a more proactive approach in IT security and threat detection. It creates a layer of protection against malicious attacks. And as they say, prevention is always better than a cure.

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