Gartner Research

Security Information and Event Management Futures and Big Data Analytics for Security

Published: 17 January 2014

ID: G00255883

Analyst(s): Anton Chuvakin , Ramon Krikken


Organizations with lean-forward security programs complement their SIEM tools with custom-built big data platforms and utilize advanced analytics for security. This assessment predicts the directions for SIEM technology and analyzes the use of big data for security today and in the near future.

Table Of Contents

Summary of Findings


  • Introduction
  • SIEM Challenges Today
    • Complexity
    • Mix of Security and Data Management
    • Performance Limits Galore
    • Data Variety Troubles
    • Real-Time Correlation, Not Data Mining
    • Analysis? Where Is That?
    • New Environment Explosion
    • Failed "Single Pane of Glass" Promises
  • Basic Extrapolations First: More of the Same
  • SIEM Futures: The Big Five
    • Expanded Context Data Collection and Analysis
    • Wider Use of Shared, Distributed Intelligence
    • Emerging Environment Monitoring
    • New and Expanded Algorithms for Historical and Real-Time Analysis
    • Application Security Monitoring Using Logs, Context and Other Data
  • Five Futures Together
  • SIEM Futures: Wild Cards
  • Use of Big Data Analytics for Security
    • Definitions
    • Motivation for Exploring Big Data Analytics for Security
    • Observed Use Cases
    • Key Success Factors and Preconditions
    • Top Challenges to Wider Adoption
    • Should You Do It?
    • How to Do It
    • SIEM and Big Data: Working Together
    • Near-Future Directions
  • Strengths
  • Weaknesses

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