User Behavior Analytics (UBA) is derived from multiple use cases of marketing and banking, where user transaction patterns are tracked to prevent fraud and abuse. This capability is now being increasingly applied to security and compliance.
Without the use of user behavior analytics (UBA), data loss prevention (DLP) solutions suffered from too many false positives and the inability to identify internal user threat patterns.
For example, a typical employee logins at 9am and if there is a pattern of VPN login sessions from different locations during the midnight hours, it is a potential disruption to the behavior patterns of the user. This issue needs to be addressed quickly before sensitive data is lost. This is a typical use case of UBA.
According to the Gartner hype cycle of Risk Management, User and Entity Behavior Analytics is at the peak of inflated expectations and would continue to rise in the next 2 to 5 years.
What is User Behavior Analytics (UBA)?
Every organization needs to protect their data against cyber-security risks but the most important threat might be the one lurking within their own organization.
Insiders with negligent intents, malicious users often have access to sensitive information.This can be exploited using any traditional security infrastructure.
User Behavior Analytics is the latest security capability that addresses this issue. It supports DLP system in an organization by detecting user action analysis. This capability is important to prevent leakage of sensitive data. It helps to detect early indicators of risk and flag inappropriate insider behavior.
If an organization is able to identify risky actions and corresponding risky user profiles – it has the necessary context to spot disgruntled and malicious employees before they leak data.
Generally, this commences by looking at user/employee access and behavior patterns across various devices, endpoints and applications. This provides a baseline of user activities. When there is a noticeable anomaly in this behavior, then the User Behavior Analytics can be used to contain that threat.
At Zecurion, this solution creates profiles of employees’ behavior based on their history of incidents in the past. The solution checks for deviations for each employee from this profile in live mode. If it detects a sudden burst for that employee it allows security teams to place the user under additional control as quickly as possible. This actionable risk ratings help security teams to detect, respond and contain a user threat in a timely manner.
What are the benefits of User Behavior Analytics?
User behavior analytics (UBA) can help with mitigating potential data losses regardless of the industry. It lowers the cost of a breach and because of it’s predictive nature, can also help in identifying potentially damaging user behavior, saving an imminent security breach.
In his blog titled, “Ok, So Who Really MUST Get a UEBA?”, Gartner analyst, Anton Chuvakin, says “An organization with a robust insider threat program should definitely get a UEBA (User and Entity Behavior Analysis).”
UBA is beneficial to provide in-depth data context with respect to location from where the users access devices belonging to the organization, what data is being accessed, what is the typical user pattern and what is the risk of the data itself.
What are the use cases of User Behavior Analytics?
- Insider Threat Detection:
This is the most common use of UBA. Insiders accidentally put data at risk – either by attaching a wrong file in an email, oversharing on social media, losing a laptop or USB, or just by using weak passwords. UBA helps to detect and classify the risk profile of employees and insider users of an organization. The focus is on risky behavior patterns and identifying access abuse and misuse.
2. Maintaining Compliance:
UBA builds on the risk management approach to information security and helps with maintaining compliance. Compliance conformance requires identifying risks and prioritizing them in order to maintain compliance. By recognizing that not all users are equal in their user behavior patterns and risk score, UBA helps an organization prioritize the analysis. It also helps with the business rules from a compliance standpoint.
3. Risk assessment tool:
UBA’s risk-scoring helps in using this as a risk assessment tool to aid in adhering to security policy and risk assessment process. If account activity profiling is linked to DLP, it can help with managing and mitigating risks. Authentication tracking and account compromise detection adds to the risk assessment of an organization.
In conclusion, User behavior analytics (UBA) is a relatively new but fast growing trend in cybersecurity. Most organizations are using UBA because of its ability to minimize false positives and identify high-risk user profiles.
UBA is a great tool to detect systems and data where compromised accounts exist.
It has multiple benefits, especially to provide additional security information that is not available through network and end point detection.
There are several use cases of UBA, the most common of them are insider threat detection, maintaining compliance and risk assessment.
Whatever is the use case, organizations are increasingly using UBA to set baselines about insider’s normal versus unusual behavior patterns, and detecting malicious insiders that leads to security insights with higher accuracy and faster detection and prevention of security breaches.