Hands-On Cyber Security Training
Discover the most effective steps to prevent cyber-attacks and detect adversaries with actionable techniques taught by top practitioners during SANS Gulf Region 2024 (2-21 November). Choose your course and register now for hands-on training you can use immediately.
SANS Gulf Region 2024 Features
- In-Person or Live Online training (see Available Courses for details)
- Practical cyber security training taught by real-world practitioners
- Hands-on labs in a virtual environment
- Courses include electronic and printed books
- Opportunity to earn CPEs to demonstrate ongoing skill development
- Most courses align with GIAC certifications to validate your knowledge
Please note, courses are available In-Person in Dubai,or Live Online during this event. Please see course details below for availability. For In-Person courses, seating is available on a first-come, first-served basis. Register now to secure your spot.
Courses are offered In-Person or Live Online.
Please see available courses for details regarding individual course delivery format.
GSEC: GIAC Security Essentials
$8,645 USD
GCIH: GIAC Certified Incident Handler
GCFA: GIAC Certified Forensic Analyst
$8,645 USD
GICSP: Global Industrial Cyber Security Professional
$9,100 USD
GSLC: GIAC Security Leadership
$8,135 USD
GMLE: GIAC Machine Learning Engineer
$8,645 USD
GSTRT: GIAC Strategic Planning, Policy, and Leadership
$8,135 USD
GCPN: GIAC Cloud Penetration Tester
$8,645 USD
GRID: GIAC Response and Industrial Defense
$9,100 USD
GSOM: GIAC Security Operations Manager
$8,135 USD
GXPN: GIAC Exploit Researcher and Advanced Penetration Tester
$8,645 USD
Class Schedule:
- 16 Nov 2024: 8:30 AM to 7:00 PM GST
- 17 Nov 2024: 9:00 AM to 7:00 PM GST
- 18 Nov 2024: 9:00 AM to 7:00 PM GST
- 19 Nov 2024: 9:00 AM to 7:00 PM GST
- 20 Nov 2024: 9:00 AM to 7:00 PM GST
- 21 Nov 2024: 9:00 AM to 5:00 PM GST
GDAT: GIAC Defending Advanced Threats
$8,645 USD
Cyber ranges
Monday, 4 November | 5:30pm-6:30pm (GST)
Most enterprises today have a number of security tools to support their security operations. In many cases, these tools have a view of what they think are bad and thus produce a large number of alerts. The problem is, the majority of these alerts tend to be false positives rather than true positives. Using machine learning, we can identify those alerts which are more likely to be true positives, thus expending more energy towards these alerts. In this session, we will discuss how you can leverage the SOAR, the SIEM (or any other security tool), Threat Intelligence and case management platforms, to build a machine learning model to aid with reducing the alert fatigue.
