Identifying Cyber Risk and Vulnerabilities in AI eLearning
This course covers Cyber Risks & Vulnerabilities and will introduce you to the concepts and key terms you need to know for a basic understanding of the unique security concerns and risks associated with AI applications. Whether your job is to Lead, Drive, Create, Facilitate, Embed, or Employ AI, this course will create a firm baseline understanding of the risks and security needs related to the continued adoption, integration, and use of AI.
Public Classroom Pricing
$25(USD)
GSA Price: $18.25
Group Rate: $25
Private Group Pricing
Have a group of 5 or more students? Request special pricing for private group training today.
Part 1: Security vs Risk
- The relationship between security and risk
- How the value of an asset affects the need for security
- How the likelihood and severity of consequences influence risk appetite
- Defense use cases where AI is being used and resulting security concerns
- Risks associated with stolen or hacked technology
- Why U.S. technological superiority is at risk because of AI
Part 2: The fours ways to Think about AI Security
- Areas of society that are vulnerable to AI-related weaknesses
- Four distinct ways to approach AI-related risk
- Examples of basic IT security problems that threaten AI
- An introduction to vulnerabilities specific to AI technology
Part 3: The limitations of AI systems
- AI’s dependence on data and limitations created as a result
- Examples of data characteristics that create specific limitations for AI
- How AI learns and operates in very narrow ways
- AI’s black box problem
- Examples of common software security problems that apply to AI
- Why the limits of AI’s narrow functionality leave it vulnerable
Part 4: Risk and vulnerabilities inherent in AI Applications
- Types of attack specific to AI technology
- AI input attacks
- AI data poisoning attacks
- Examples of how AI attacks operate
- How increasing AI use creates a distinct attack surface
- Risks and vulnerabilities created as a result of how AI is being used
Part 5: How Attackers are Leveraging AI and Machine Learning
- The risks of hostile AI
- Adversarial machine learning as a security risk
- How hostile AI magnifies the risk of existing AI vulnerabilities
- Common goals of an attacker
- Examples of how AI-related attacks achieve an attacker’s goals
Part 6: Implementing better security and How AI and Machine Learning can help
- Key concepts of IT automation
- Four questions to identify opportunities for AI to help with security
- IT security needs well suited for improvement through automation and AI
- Specific types of IT automation made possible by AI
- How AI can help identify vulnerabilities and threats
- Examples of how data visualization can help with AI-related security concerns
Part 7: Final assessment
Professionals who would benefit from this training include:
- Cybersecurity Analyst
- Vulnerability Analyst
- IT Auditor
- IT Risk Manager
- Vulnerability Analyst
- IT Manager
- Security Ops Analyst
- Understand Security vs. Risk
- Learn four ways to think about AI security
- Review limitations of AI systems
- Learn about particular risks and vulnerabilities inherent in AI applications
- Understand how attackers are using - or could use - AI and Machine Learning against us
- Learn how to implement better security, and learn how AI/ML can help