Detecting Insider Threats: Leverage User Behavior Analytics

Detecting Insider Threats: Leverage User Behavior Analytics

Employees often play an unwitting role in many security incidents, from accidental data breaches to intentional malicious attacks. Unfortunately, most organizations don’t have the right protocols and processes to identify potential risks posed by their workforce.

Based on a survey conducted by SANS Institute, 35% of respondents said they lack visibility into insider threats, while 30% said the inability to audit user access is a security blind spot in their organizations. In addition, the 2023 X-Force Threat Intelligence Index reported that 41% of security incidents involved phishing for initial access.


This means that organizations are vulnerable to costly and damaging security incidents caused by their own people — whether through negligence or deliberate intent. Detecting insider threats is challenging for many security teams, and traditional security measures are no longer sufficient to address this issue. However, by leveraging user behavior analytics (UBA), organizations can detect and prevent insider threats more effectively.


What is User Behavior Analytics?


User behavior analytics (UBA) is a security software that detects unusual behavior and anomalies in user activity by collecting various data types. UBA uses machine learning, automation and artificial intelligence to analyze data from various sources, such as logs, network traffic and endpoint devices, to create a baseline of normal user behavior. UBA then monitors behavior in real-time and alerts security teams when it detects anomalies that could indicate an insider threat.


Benefits of User Behavior Analytics in Detecting Insider Threats


UBA provides detecting insider threats leverage behavior analytics