Table of Content
- Introduction
- How UEBA Works
- How to use UEBA to Uncover Hidden & Hard-to-Detect Threats
- Conclusion
Introduction
As organizations continue to face a growing number of sophisticated and complex threats, the need for effective security solutions become increasingly important. One tool that has proven to be effective in detecting hidden and hard-to-detect threats is the User and Entity Behavior Analytics (UEBA) solution.
UEBA uses machine learning and advanced analytics to analyze user behavior and identify anomalies that may indicate a potential threat. It allows organizations to detect threats that may not be immediately obvious, such as when an attacker uses a legitimate user's account to gain access to sensitive data. So, this way it helps in identifying unusual activities or suspicious user behavior that are very different to the normal day pattern or activities and alert the same to the IT administrators and security analysts for further investigation.
Covering more on this in detail, we have in the article explained how UEBA works and how exactly UEBA can help uncover hidden & hard to detect threats. But before that let us get some kind of understanding on the way a UEBA solution works.
How UEBA Works
User and Entity Behavior Analytics (UEBA) is a one of a kind cybersecurity solution that uses advanced Machine Learning (ML) capabilities and algorithms to analyze and detect anomalies.
The solution takes the SOC's monitoring and detection mechanisms a level up with its capabilities of detecting unusual activities or anomalies and complex attacks across various devices in the network. Leveraging the machine learning capabilities to monitor and analyze user activities online, UEBA helps identify unusual and abnormal user behaviour in the network.
Collecting data about user activities and their devices from various log sources, the system uses advanced analytical models and ML capabilities to analyze the current data against an established baseline of normal user behavior patterns. Based on these baseline patterns, UEBA monitors and compares the entity behavior to identify unusual activities and potential threats.
The baseline established forms the key to analyzing and detecting potential threats. Further, the system compares the user behavior with the established baseline to calculate the risk score and determine whether or not the identified deviation is acceptable. So, when there is slightest deviation from those established baseline patterns, such anomalies are further analyzed and accordingly system alerts are generated to the security analysts in real time.
UEBA monitors and detects even the most subtle difference and creates a baseline comparison to identify abnormal network activities. This increases the level of accuracy and reduces the rate of false positives while significantly increasing the overall security operational efficiency in the SOC.
How to Use UEBA to Uncover Hidden & Hard-to-Detect Threats
1. Real-time Monitoring & Analysis
UEBA collects data and monitors users and devices connected to the environment on a real time basis. This allows for quick comparison and identification of unusual patterns, and analysing and correlating of events. By continuously monitoring the current user behavior with established baseline patterns of normal user behavior, UEBA identifies anomalies in real-time, and facilitates immediate generation of alerts to the security analysts. Such real-time monitoring and analysis results in minimal delay in response to potential threat and prevention or minimal impact of an attack.
2. ML & Advanced Analytics Driven Detection Capabilities
UEBA has the ability to detect even the slightest deviation in user behavior that may indicate a security threat or an insider attack. So, typically instead of applying predefined rules for standard behavior, UEBA proactively detects potential threats by leveraging ML and advanced analytical capabilities. This helps in quick detection of unknown threats in real time which may otherwise go unnoticed.
The detection of such unusual behavior or anomalous patterns is possible even in cases where such attack patterns are unknown and have never been observed before. This is particularly important given the increasing prevalence of attacks that are designed to evade traditional security solutions. However, It is important for organizations to regularly review and update their baseline of normal user behavior. This will ensure that UEBA can accurately identify potential threats and prevent false positives.
3. Collaborative Analysis of Security Events
UEBA has the ability to identify and correlate security events and/or incidents across multiple users, devices, and applications. Collecting data from various sources, the system combines all the data into a single console for further data analysis and correlation. Such collaborative and insightful data helps in quick detection, analysis and investigation of identified anomalies or potential threats.
4. Enriched & Insightful Data
UEBA and SIEM integrations facilitate effective data correlation, making the data analysis of events more insightful than ever before. With the integration, the log data can be enriched, enabling correlation and visualizing of events using dashboards and search templates. This helps the security analyst with faster and accurate threat hunting and discovering of suspicious user behavior.
Read : How UEBA can help Identify and prioritize potential threats in an organization
Conclusion
UEBA is a valuable tool for organizations looking to detect hidden and hard-to-detect threats. Organizations can effectively identify and mitigate potential threats, while also gaining valuable insights into user behavior. Such advanced analytics and insightful data helps the security team build robust security measures and improve the overall security posture of the organization.
DNIF HYPERCLOUD is a cloud-native SIEM solution (Security Information and Events Management) that comes with in-built UEBA and automation capabilities. With DNIF HYPERCLOUD organizations can ingest large volumes really fast, with extremely low infra footprint. The UEBA capability helps security teams in detecting suspicious activity using Machine Learning and No Code Outlier Detection and find unknown scenarios on the enterprise scale. Book A Demo to know how DNIF HYPERCLOUD can strengthen your security posture at low cost.
