Overview
The evolution of Gartner UEBA & UEBA Meaning:
What is UEBA Security, UEBA baselines user behavior and entity behavior activities, and combines it with peer group analysis, and then searches for and analyzes anomalous activity in order to detect potential or actual intrusions and malicious activity.
UEBA goes beyond fact-based security and simple correlation rules, and leverages both user behavior and entity behavior-based analytics, and models threats based on individual user behaviors.
Why UEBA Security improves UBA and legacy SIEMs :
User behavior and Entity Behavior Analytics represents an important improvement over UBA and legacy SIEM systems for a number of reasons. First, it overcomes the limitations of SIEM correlation rules—and the reality that in many cases the whole model of correlation rules is broken. Some of the problems associated with relying on SIEM correlation rules include:- You can’t find attacks because the rules lack context, or miss incidents that have never been seen before, thus generating false negatives.
- Rules require too much maintenance.
- Improperly filtered rules can make incident response execution slow because administrators need to filter the application of rules to determine which data is relevant, and which data is irrelevant in your event landscape.
Key Features
Data
Integration
Easily compile data from event logs deep packet inspection, and outside threat intelligence, attribute behaviours and create master database containing all communications within the network to establish baseline. Use this baseline to later pinpoint deviations indicating malicious intent.
ML Enabled
Analytics
With Machine learning abilities to enable user and entity behaviors modelling and analytics based on various organizational components. With real time security events and ML, detect and prevent threats that traditional tools miss.
Reduce False
Positives
Building profiles for each entity, UEBA uses context surrounding behaviors to differentiate between attacks and false positives.
Key Benefits
Detection of Hijacked Accounts
Attackers who steal valid user credentials behave differently than real users. UEBA uses real-time detection to ascertain if something is out of norm and responds to the threat through various real-time responses such as Block, Modify, Re-authenticate or Multi-factor authentication. This ensures that the real threats are getting addressed before they try to harm the system.
Reduced Attack Surface
UEBA sends insights to the users and the security teams through interactive analytics which allows them to know about the loopholes or weak points before an incident happens. These insights help reduce the attack surface which makes it difficult for the cyber attacker to breach the network.
Privilege Abuse and Misuse
In any organization the privileged users have extensive access to the system, data and applications which is why they present a higher risk to the organization. UEBA’s algorithms ensure that the access rights are used appropriately and give an overview of what kind of privileges individual users should have.
Improved Operational Efficiency
It takes a lot of efforts to identify threats manually through alerts. UEBA can manually identify and validate threat without manual intervention through automation and security intelligence. This level of automation allows security to focus on real threats rather than alert chasing.
Data Exfiltration Detection
UEBA analytics help to detects potential data exfiltration before
it happens, thus allowing businesses time to prepare a strategic
plan to prevent data theft. It can even help identify Advanced
Persistent Threats (APT).
UEBA has proved itself to be an
indispensable asset in the world of cyber security. According
to experts user and entity behavior analytics is a better model
for attack detection and maintain that it is going to enable more
accurate detection of cyber attackers threatening networks.
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