Gartner Research

A Comparison of UEBA Technologies and Solutions

Published: 29 March 2017

Summary

UEBA utilizes machine learning and other advanced analytics to detect threats and simplify the work of technical professionals focused on security. This research contrasts top UEBA technologies based on use cases and capabilities and highlights common usage scenarios and tool evaluation processes.

Included In Full Research

  • Comparison Criteria
  • UEBA Solution Use Cases Comparison
  • UEBA Tool Capabilities
    • Capability Summary
  • Capability Comparison
  • UEBA Defined
  • Generic UEBA Product Architecture
  • UEBA Products vs. UEBA Capabilities
    • Just How Smart Is UEBA?
    • UEBA Drivers and Business Case
  • The UEBA Market
    • SIEM vs. UEBA
    • SIEM With UEBA
    • Open-Source Alternatives
  • UEBA Trends and Future
  • Organizations Benefiting From UEBA
  • Challenges With UEBA
    • Data Collection: Availability and Quality
    • Different Expert Labor
    • Tool Tuning Challenges
    • Proving Future Detection From Low-Criticality Examples
    • Alert, Incident and Anomaly Response Process
    • Effectiveness Measurement Challenges
    • Performance Problems Around Collection
    • Challenges Baselining Messy IT Environments
    • Cross-Silo Nature of UEBA
    • Privacy Challenges
  • Building a Business Case for UEBA
  • Selecting UEBA Tools
    • UEBA Selection Focus Areas
  • Deploying UEBA
  • Use-Case Assessment Criteria
  • Vendor Profiles
    • Exabeam
    • Gurucul
    • Interset
    • Niara
    • Securonix
    • Splunk
  • Running a UEBA POC

Analyst(s): Augusto Barros Anton Chuvakin

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