SANS SIEM Summit & Training

October 7th, 2019

 October 7th, 2019 - October 14th, 2019 

SANS SIEM Summit & Training

United States  »  Midwest, USA  »  Illinois » 
October 7th, 2019 - October 14th, 2019

Event Website

InfoSec Conference Summary

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Bring order to data chaos.

Security teams continue to miss intrusions that can be easily detected with the data and logging solutions they already have. While many security programs deploy a Security Information and Event Management (SIEM) platform, they struggle to effectively collect, parse, enrich, and filter the vast amounts of data they’re collecting. This ultimately leads to a failure to generate actionable intelligence and detect intrusions before it’s too late. Instead of following the tradition of centrally collecting data to more efficiently ignore it, attend the SIEM Summit and bring order to the chaos by learning how to use your data for tactical analysis and detection.

Hear from the experts and find out how to turn adversary strengths into weaknesses.

The SIEM Summit will provide participants with practical approaches and techniques that enable organizations to use their SIEM platform as a robust detection capability. The Summit will bring together leading security experts and present real-world case studies that demonstrate how to leverage new or existing high-value log sources. With its focus on the effective use of monitoring tools and sound analysis techniques, the Summit aims to cure SIEM deployments of their most common issues and pass on the newest ideas about how to better utilize the advanced capabilities of these platforms. Join us to learn first-hand from those who are effectively using their SIEM platform to identify, detect, and ultimately hunt adversaries.

The Summit will also discuss the following topics:

  • Detection techniques and tools
  • Log collection
  • Log enrichment (pre-ingestion or post-ingestion)
  • Log analysis with emphasis on adversary detection
  • Scripts that provide cool new ways of analyzing data
  • Security in Continuous Monitoring
  • Data Processing, Normalization, and Analysis
  • Applying security expertise to data analytics
  • False positive reduction
  • Machine learning and statistical data analysis

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