Protecting Your Organization from Insider Threats

  • Overview
  • Course Content
  • Requirements & Materials
Overview

Protecting Your Organization from Insider Threats

Course Description

Artificial intelligence is transforming the insider threat landscape as both a vulnerability and a capability. This two-day course examines AI systems as high-value targets for insider attacks while teaching participants to leverage AI-powered detection tools. Day 1 explores AI-specific threat vectors including data poisoning, model theft, and infrastructure compromise. Day 2 focuses on implementing behavioral analytics, predictive detection, and program adaptation frameworks. Led by GTRI insider threat and cybersecurity experts, participants gain hands-on experience through labs, case studies, and workshops. You'll leave with policy templates, phased implementation roadmaps, and executive briefing frameworks ready for immediate application in government, defense, or industry organizations facing AI security challenges.

Course Content

AI FUNDAMENTALS & THREAT LANDSCAPE
• Introduction to insider threat and AI/ML fundamentals
• AI assets requiring protection
• AI development lifecycle and attack surfaces
• The insider advantage in AI environments

AI-SPECIFIC THREAT VECTORS
• Ten major AI insider threat types
• Data poisoning and training data theft
• Model theft and backdoor insertion
• Infrastructure abuse and IP exfiltration

DATA-CENTRIC INSIDER THREATS
• Training data poisoning techniques
• Data exfiltration and privacy violations
• Data pipeline sabotage
• Detection challenges and mitigation

MODEL & INFRASTRUCTURE THREATS
• Model theft and intellectual property protection
• Model backdoor insertion and sabotage
• AI infrastructure compromise
• Case study analysis

AI-POWERED DETECTION CAPABILITIES
• User and Entity Behavior Analytics (UEBA)
• Behavioral baselines and anomaly detection
• ML pipeline monitoring
• Predictive analytics for investigation

PROGRAM ADAPTATION FRAMEWORK
• Eight-pillar AI security assessment
• Gap analysis and policy development
• Phased implementation roadmap
• Quick wins and long-term strategy

LEADERSHIP & GOVERNANCE
• Executive leadership engagement strategies
• Building security-positive culture
• Seven-phase culture transformation
• AI governance frameworks

Requirements & Materials

Materials

PROVIDED (Student will receive):

Frameworks & Templates:

  • Eight-pillar AI security assessment framework
  • Phased implementation roadmap (18-month plan)
  • AI asset protection policy templates
  • Gap analysis worksheets
  • Executive briefing frameworks

Reference Materials:

  • Course slides and handouts
  • Case study documentation

Resource lists and reading materials

Session Details

  • Special Discounts: Georgia Tech Research Institute (GTRI) employees are eligible to receive a discount.  If you are a GTRI employee, please go to the Organizational Development website and look for the coupon code under GT Professional Development. Review coupon instructions for more information.

Who Should Attend

This course is designed for insider threat program managers, security operations personnel, AI/ML security professionals, risk management professionals, compliance officers, CISO and security leadership, and government and defense personnel responsible for protecting sensitive information and AI systems. This course is accessible to both technical and non-technical professionals; no programming experience or deep AI technical expertise is required.

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What You Will Learn

  • AI-specific insider threat vectors including data poisoning, model theft, and infrastructure attacks
  • Data-centric threats to training data, datasets, and privacy
  • AI-powered detection using UEBA and behavioral analytics
  • Predictive analytics for proactive threat investigation
  • Eight-pillar program adaptation framework and implementation roadmaps
  • Executive leadership engagement strategies
  • AI asset protection policy development
Cybersecurity professional working on computer

How You Will Benefit

• Identify and mitigate 10+ AI-specific insider threat vectors protecting high-value AI assets from data poisoning, model theft, and infrastructure attacks.
• Implement behavioral analytics (UEBA) systems detecting subtle anomalies and insider threat patterns.
• Deploy predictive analytics for proactive threat identification and investigation.
• Build phased implementation roadmaps with quick wins and long-term transformation plans.
• Secure executive leadership support using proven frameworks demonstrating business value.
• Create actionable AI protection policies using templates and gap analysis tools.

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    Taught by Experts in the Field

The course schedule was well-structured with a mix of lectures, class discussions, and hands-on exercises led by knowledgeable and engaging instructors.

- Abe Kani
President

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