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Certified - AI Security Audio Course
Jason Edwards
51 episodes
6 days ago
The AI Security & Threats Audio Course is a comprehensive, audio-first learning series focused on the risks, defenses, and governance models that define secure artificial intelligence operations today. Designed for cybersecurity professionals, AI practitioners, and certification candidates, this course translates complex technical and policy concepts into clear, practical lessons. Each episode explores a critical aspect of AI security—from prompt injection and model theft to data poisoning, adversarial attacks, and secure machine learning operations (MLOps). You’ll gain a structured understanding of how vulnerabilities emerge, how threat actors exploit them, and how robust controls can mitigate these evolving risks. The course also covers the frameworks and best practices shaping AI governance, assurance, and resilience. Learners will explore global standards and regulatory guidance, including NIST AI Risk Management Framework, ISO/IEC 23894, and emerging organizational policies around transparency, accountability, and continuous monitoring. Through practical examples and scenario-driven insights, you’ll learn how to assess model risk, integrate secure development pipelines, and implement monitoring strategies that ensure trust and compliance across the AI lifecycle. Developed by BareMetalCyber.com, the AI Security & Threats Audio Course blends foundational security knowledge with real-world application, helping you prepare for advanced certifications and leadership in the growing field of AI assurance. Explore more audio courses, textbooks, and cybersecurity resources at BareMetalCyber.com—your trusted source for structured, expert-driven learning.
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All content for Certified - AI Security Audio Course is the property of Jason Edwards and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
The AI Security & Threats Audio Course is a comprehensive, audio-first learning series focused on the risks, defenses, and governance models that define secure artificial intelligence operations today. Designed for cybersecurity professionals, AI practitioners, and certification candidates, this course translates complex technical and policy concepts into clear, practical lessons. Each episode explores a critical aspect of AI security—from prompt injection and model theft to data poisoning, adversarial attacks, and secure machine learning operations (MLOps). You’ll gain a structured understanding of how vulnerabilities emerge, how threat actors exploit them, and how robust controls can mitigate these evolving risks. The course also covers the frameworks and best practices shaping AI governance, assurance, and resilience. Learners will explore global standards and regulatory guidance, including NIST AI Risk Management Framework, ISO/IEC 23894, and emerging organizational policies around transparency, accountability, and continuous monitoring. Through practical examples and scenario-driven insights, you’ll learn how to assess model risk, integrate secure development pipelines, and implement monitoring strategies that ensure trust and compliance across the AI lifecycle. Developed by BareMetalCyber.com, the AI Security & Threats Audio Course blends foundational security knowledge with real-world application, helping you prepare for advanced certifications and leadership in the growing field of AI assurance. Explore more audio courses, textbooks, and cybersecurity resources at BareMetalCyber.com—your trusted source for structured, expert-driven learning.
Show more...
Courses
Education,
Technology
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Episode 40 — Content Provenance & Watermarking
Certified - AI Security Audio Course
26 minutes
1 month ago
Episode 40 — Content Provenance & Watermarking

This episode examines content provenance and watermarking as methods to authenticate AI-generated or human-created content, providing assurance of originality and integrity. Provenance involves tracking the history and origin of digital assets, often through metadata or cryptographic proofs, while watermarking embeds identifiable signals into content to mark it as genuine. For certification exams, learners must know these definitions, their role in addressing synthetic media risks, and how frameworks such as the Coalition for Content Provenance and Authenticity (C2PA) aim to standardize authenticity signals. The exam relevance lies in connecting these mechanisms to security and compliance objectives.

Applied perspectives include watermarking text or images to flag AI-generated outputs, embedding provenance metadata in media pipelines, and deploying cryptographic integrity checks to confirm content authenticity. Best practices emphasize combining provenance with watermarking to increase resilience, while troubleshooting scenarios highlight vulnerabilities such as metadata stripping or watermark removal. For learners, exam readiness means explaining the strengths and limitations of each approach, recognizing the operational role of standards, and articulating how provenance supports trust in AI-driven content ecosystems. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your certification path.

Certified - AI Security Audio Course
The AI Security & Threats Audio Course is a comprehensive, audio-first learning series focused on the risks, defenses, and governance models that define secure artificial intelligence operations today. Designed for cybersecurity professionals, AI practitioners, and certification candidates, this course translates complex technical and policy concepts into clear, practical lessons. Each episode explores a critical aspect of AI security—from prompt injection and model theft to data poisoning, adversarial attacks, and secure machine learning operations (MLOps). You’ll gain a structured understanding of how vulnerabilities emerge, how threat actors exploit them, and how robust controls can mitigate these evolving risks. The course also covers the frameworks and best practices shaping AI governance, assurance, and resilience. Learners will explore global standards and regulatory guidance, including NIST AI Risk Management Framework, ISO/IEC 23894, and emerging organizational policies around transparency, accountability, and continuous monitoring. Through practical examples and scenario-driven insights, you’ll learn how to assess model risk, integrate secure development pipelines, and implement monitoring strategies that ensure trust and compliance across the AI lifecycle. Developed by BareMetalCyber.com, the AI Security & Threats Audio Course blends foundational security knowledge with real-world application, helping you prepare for advanced certifications and leadership in the growing field of AI assurance. Explore more audio courses, textbooks, and cybersecurity resources at BareMetalCyber.com—your trusted source for structured, expert-driven learning.