What is User and Entity Behavior Analytics (UEBA)?

Last Updated : 21 Apr, 2025

User and Entity Behavior Analytics (UEBA) known as the innovative cybersecurity approach that employs intelligent algorithms and machine learning to recognize uncustomary behaviors within networks instead of keeping threats out like conventional security technologies do. UEBA is very useful for a variety of cybersecurity situations detection of insider threats, abnormal behavior from employees, or insiders who may be unauthorized or abusing company resources can be found very easily.

UEBA represents User and Entity Behavior Analytics. This is a type of cybersecurity technology that is used to monitor user behavior as well as devices on networks by detecting anomalous actions that may suggest security threats. In this article, we will learn about UEBA, how UEBA works, use cases of UEBA, and the difference between SIEM, UEBA, and NTA.

What is UEBA?

User and Entity Behavior Analytics (UEBA) is a cutting-edge cybersecurity approach that uses smart algorithms and machine learning to spot unusual activities across networks. This type of cybersecurity detects suspicious activities within networks (Miele, 2017). It doesn’t focus on preventing threats ie. keeping them out, but rather aims to check how effectively users operate inside the network by analyzing all possible variables around them, before major consequences occur or after they have increased into serious problems it may be too late to handle easily without incurring huge losses to the organization.

Such disruptive innovations would help in preventing incoming disasters, thereby providing insurance coverage against massive loss through unavoidable operational breakdowns due to ignorance or malfunctioning operations caused by human carelessness, committed while using applications by staff members at various companies’ departments on shared servers.

How UEBA Works?

UEBA functions through constantly amassing and appraising vast amounts of information on user behaviors within applications, traffic patterns across networks as well as device operations. By implementing artificial intelligence technology, UEBA establishes the characteristic behavior of an individual or system at any given time. If at all there is a variation from this pattern say different data accesses that are not by one’s job description but need to be finished, uncommon attempts to access login credentials instead of pretending to be somebody else alongside abnormal usage regarding applications, UEBA makes us aware of potential hazards using the red flag mechanism in informing our safety groups.

UEBA Use Cases

UEBA is very helpful for detection of compromised accounts that takes place within no time if one logs his information. UEBA is valuable in a range of cybersecurity scenarios.

Spotting Insider Threats: Being able to spot when employees or insiders are behaving abnormally indications that they could have gained unauthorized entry into an organization’s systems or resources.

Identifying Compromised Accounts: Recognizing strange login activities or attempts to access sensitive data, this might mean that someone has had his or her login details stolen.

Intrusion Detection: Looking out for immediate spikes in data downloads or abnormal traces in network traffic is known as anomaly detection to check for possible breaches or infections.

SIEM vs UEBA vs NTA

SIEM	UEBA	NTA
Systems for Security Information and Event Management (SIEM) are designed in a way such that they aggregate and correlate information gathered from a variety of sources in an organization's IT infrastructure. Their purpose is to analyze log data originating from servers, applications network devices as well as security controls so as to identify any security incidents, policy breaches or operational matters.	User and Entity Behavior Analytics solutions are good at monitoring the behavior of users and devices (like devices, apps) inside a corporate network, creating normal behavior patterns with help of machine learning and statistics and finding deviations seen as a sign of insider threats, hacked accounts or other unmatched activities.	NTA solutions are made for observing and studying the network traffic to monitor and analyze it. They specialize in intercepting and investigating network packets or flow data to find any unusual or criminal deeds inside the network like network incursions, data exfiltration, or lateral movement by attackers.
It usually picks up data from various sources like servers, firewalls, Intrusion Detection Systems and malware protection systems.')	It examines information from a variety of places like logs, endpoints, applications and network devices and is particularly interested in how people and things behave.	Focuses on network traffic data. Capture and analyze network packets or flow records from routers, switches and other network devices.
It is possible to identify security breaches by correlating incidents occurring in various places, to reveal irregularities or patterns pointing to possible dangers.	It identifies irregular user behaviors or entity behaviors that are suggestive of security threats, like queer logins times, too much accessing files etc.	Detecting suspicious network activities can be performed by analyzing traffic patterns, anomalies in packet headers or deviations from established baseline network behaviour.
This can be used for real time tracking, fraud reply, obedience supervision and inspection investigation in the whole IT infrastructure of a firm.	Utilized for the identification of insider threats, compromised accounts, account takeovers, and other abnormalities that the ordinary measures for security cannot detect.	It is mainly used for network visibility, detecting threats in networks, and recognizing potential network attacks.
Is used mainly for security operations as it integrates well with other tools and gives a complete picture of an organization’s security position.	It could work alone, or by teaming up with SIEMs and other security products to increase in user-focused detection and response features for threats.	Typically it can act alone, but usually affiliates with SIEMs, giving security analysts supplementary context and network visibility.

How UEBA Enables Faster Threat Detection?

Cyber Threat Intelligence aims for understanding threat origins and improving defenses, how can it reduce the complexity of understanding threats flagged in the system as important. Therefore, making it easier for human analysts to understand them.

Understanding Normal Behavior: UEBA spots what is normal for any individual or instrumentality in view of their past activities, for example typically when they log in, which files they would often access or mode of interaction they would always employ towards other persons in a network.

Detecting Unusual Behavior: It uses intelligent software for recognizing unusual activities happening in the present time. A case in point is when an individual logs in from an unfamiliar place or accesses confidential data which are hardly accessible. In such cases, UEBA responds by alerting the user.

End to end Security: UEBA does more than just focus on one person or device, it looks at everyone’s behavior patterns. It is capable of spotting such coordinated attacks if several users start behaving oddly at once or similarly.

Conclusion

User and Entity Behavior Analytics (UEBA) is a great way to improve cybersecurity with the help of analyzing strange behaviours that happen in a network. It involves analyzing unusual behaviours across networks for purposes such as finding out whether there are any patterns or not which deviates from what can be considered usual among users as well as devices. Due to this fact, identifying abnormalities or possible hazards can be done quickly thus preventing conventional security systems from overlooking them.