From the course: CompTIA SecAI+ (CY0-001) Cert Prep
About the SecAI+ exam
From the course: CompTIA SecAI+ (CY0-001) Cert Prep
About the SecAI+ exam
AI is reshaping every corner of modern business. From intelligent assistance and predictive models to automated decision-making, today's organizations rely on AI and the data that fuels it to create business value. But with that value comes new risk, model abuse, data poisoning, prompt injection, privacy leaks, and governance challenges. We must secure AI systems end-to-end. That creates a tremendous need for skilled professionals who can build, assess, and protect AI solutions. CompTIA's SEC AI Plus certification allows you to demonstrate that you understand AI concepts, that you have the ability to secure AI systems, that you can use AI to support security operations, and that you understand the governance, risk, and compliance issues associated with AI. Hi, I'm Mike Chappell. I've been working in the cybersecurity field for over 25 years. And I'm Fredwang Ganga. I'm an expert in machine learning and artificial intelligence. We're the authors of the Cybex Study Guide for the CompTIA SecAI Plus exam. In this course, we'll work together to share our expertise in the world of AI security. We'll discuss basic AI concepts, securing AI systems, using AI to improve cybersecurity, and the governance, risk, and compliance issues associated with artificial intelligence. All right, let's get rolling.
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Contents
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The AI lifecycle1m 39s
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Business alignment in the AI lifecycle1m 43s
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Data collection2m 20s
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Data preparation3m 15s
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Model development and selection2m 13s
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Model evaluation and validation2m 29s
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Model deployment and integration3m 25s
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Monitoring and maintenance3m 19s
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Manipulating application integrations4m 8s
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AI supply chain attacks2m 4s
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Insecure plug-in design2m 9s
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Insecure output handling1m 23s
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Output integrity attacks2m 8s
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Model denial of service1m 31s
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Excessive agency1m 33s
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Overreliance1m 34s
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AI hallucinations1m 4s
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Monitoring prompts and responses2m 51s
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Log monitoring4m 30s
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Rate and cost monitoring5m 1s
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Auditing for AI hallucinations3m 33s
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Auditing for accuracy3m 29s
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Auditing for bias and fairness4m 35s
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Auditing access and security compliance3m 48s
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Responsible AI5m 29s
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AI risks2m 23s
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Introduction of bias2m 37s
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Accidental data leakage2m 53s
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Reputational loss2m 11s
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Accuracy and performance of the model2m 22s
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Intellectual property risks3m 31s
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Autonomous systems2m 27s
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Shadow IT and shadow AI1m 48s
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Awareness training2m 21s
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