User behavior analytics

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User behavior analytics (UBA) is a cybersecurity process about detection of insider threats, targeted attacks, and financial fraud that tracks a system's users. UBA looks at patterns of human behavior, and then analyzes them to detect anomalies that indicate potential threats.[1][2] Big data platforms like Apache Hadoop are increasing UBA functionality by analyzing petabytes worth of data to detect insider threats and advanced persistent threats.[3][4]

Purpose[edit]

UBA's purpose, according to Johna Till Johnson of Nemertes Research, is that "Security systems provide so much information that it's tough to uncover information that truly indicates a potential for real attack. Analytics tools help make sense of the vast amount of data that SIEM, IDS/IPS, system logs, and other tools gather. UBA tools use a specialized type of security analytics that focuses on the behavior of systems and the people using them. UBA technology first evolved in the field of marketing, to help companies understand and predict consumer-buying patterns. But as it turns out, UBA can be extraordinarily useful in the security context too."[5]

See also[edit]

References[edit]

  1. ^ Market Guide for User Behavior Analytics
  2. ^ The hunt for data analytics: Is your SIEM on the endangered list?
  3. ^ Ahlm, Eric; Litan, Avivah (26 April 2016). "Market Trends: User and Entity Behavior Analytics Expand Their Market Reach". Gartner. Retrieved 15 July 2016.
  4. ^ "Cybersecurity at petabyte scale". Retrieved 15 July 2016.
  5. ^ User behavioral analytics tools can thwart security attacks

External links[edit]