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Risks and Cybersecurity in Generative AI

IT & Software

Risks and Cybersecurity in Generative AI, available at $44.99, has an average rating of 4.7, with 17 lectures, based on 5 reviews, and has 546 subscribers.

Rating4.7
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You will learn about Understand the core concepts of generative AI and associated cybersecurity risks. Identify and analyze potential vulnerabilities within AI systems. Learn strategies to mitigate risks including data poisoning and model bias. Explore ethical considerations and best practices in AI development and usage. This course is ideal for individuals who are Technology Professionals: IT professionals, cybersecurity analysts, and software developers looking to deepen their knowledge of AI-specific security challenges will benefit from this course. It provides the tools and insights needed to safeguard AI systems within their organizations. or AI and Machine Learning Enthusiasts: Individuals with a keen interest in artificial intelligence and machine learning who wish to understand the potential risks and ethical considerations associated with these technologies will find this course enriching. or Students and Academics: Undergraduate and graduate students studying computer science, artificial intelligence, or cybersecurity, as well as academics and researchers in these fields, will gain from the detailed exploration of AI vulnerabilities and mitigation strategies. or Business Leaders and Managers: Executives and managers overseeing AI projects or considering AI implementations in their business operations will learn how to assess risks and implement effective security protocols to protect company data and AI investments. It is particularly useful for Technology Professionals: IT professionals, cybersecurity analysts, and software developers looking to deepen their knowledge of AI-specific security challenges will benefit from this course. It provides the tools and insights needed to safeguard AI systems within their organizations. or AI and Machine Learning Enthusiasts: Individuals with a keen interest in artificial intelligence and machine learning who wish to understand the potential risks and ethical considerations associated with these technologies will find this course enriching. or Students and Academics: Undergraduate and graduate students studying computer science, artificial intelligence, or cybersecurity, as well as academics and researchers in these fields, will gain from the detailed exploration of AI vulnerabilities and mitigation strategies. or Business Leaders and Managers: Executives and managers overseeing AI projects or considering AI implementations in their business operations will learn how to assess risks and implement effective security protocols to protect company data and AI investments.

Enroll now: Risks and Cybersecurity in Generative AI

Summary

Title: Risks and Cybersecurity in Generative AI

Price: $44.99

Average Rating: 4.7

Number of Lectures: 17

Number of Published Lectures: 17

Number of Curriculum Items: 17

Number of Published Curriculum Objects: 17

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Understand the core concepts of generative AI and associated cybersecurity risks.
  • Identify and analyze potential vulnerabilities within AI systems.
  • Learn strategies to mitigate risks including data poisoning and model bias.
  • Explore ethical considerations and best practices in AI development and usage.

Who Should Attend

  • Technology Professionals: IT professionals, cybersecurity analysts, and software developers looking to deepen their knowledge of AI-specific security challenges will benefit from this course. It provides the tools and insights needed to safeguard AI systems within their organizations.
  • AI and Machine Learning Enthusiasts: Individuals with a keen interest in artificial intelligence and machine learning who wish to understand the potential risks and ethical considerations associated with these technologies will find this course enriching.
  • Students and Academics: Undergraduate and graduate students studying computer science, artificial intelligence, or cybersecurity, as well as academics and researchers in these fields, will gain from the detailed exploration of AI vulnerabilities and mitigation strategies.
  • Business Leaders and Managers: Executives and managers overseeing AI projects or considering AI implementations in their business operations will learn how to assess risks and implement effective security protocols to protect company data and AI investments.

Target Audiences

  • Technology Professionals: IT professionals, cybersecurity analysts, and software developers looking to deepen their knowledge of AI-specific security challenges will benefit from this course. It provides the tools and insights needed to safeguard AI systems within their organizations.
  • AI and Machine Learning Enthusiasts: Individuals with a keen interest in artificial intelligence and machine learning who wish to understand the potential risks and ethical considerations associated with these technologies will find this course enriching.
  • Students and Academics: Undergraduate and graduate students studying computer science, artificial intelligence, or cybersecurity, as well as academics and researchers in these fields, will gain from the detailed exploration of AI vulnerabilities and mitigation strategies.
  • Business Leaders and Managers: Executives and managers overseeing AI projects or considering AI implementations in their business operations will learn how to assess risks and implement effective security protocols to protect company data and AI investments.

The course “Risks and Cybersecurity in Generative AI” offers a comprehensive exploration into the intersection of artificial intelligence and cybersecurity. This course is designed to provide you with a thorough understanding of the potential risks and security measures necessary for deploying generative AI technologies safely and responsibly.

Starting with an introduction to the basics of AI and generative models, you will learn about the broad applications and benefits of generative AI, followed by an initial look at AI security considerations. The course progresses into a detailed examination of core cybersecurity risks such as data privacy, breaches at AI service providers, and the evolution of threat actors, equipping you with strategies to protect sensitive information and mitigate risks.

Further, you will delve into specific attack vectors and vulnerabilities unique to AI, including data leakage, prompt injections, and the challenges of inadequate sandboxing. Each module is structured to provide practical knowledge through real-world examples and demonstrative sessions, enhancing your learning experience.

The course also addresses network-level risks and AI-specific attacks, covering critical areas like Server Side Request Forgery (SSRF), DDoS attacks, data poisoning, and model bias. The final modules focus on legal and ethical considerations, guiding you through navigating intellectual property challenges and promoting ethical guidelines in AI development and usage.

By the end of this course, you will be well-prepared to assess, address, and advocate for robust cybersecurity practices in the field of generative AI, ensuring these technologies are developed and deployed with the highest standards of security and ethical considerations.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: Introduction to Generative AI

Chapter 2: Core Cybersecurity Risks in Generative AI

Lecture 1: Core Cybersecurity Risks in Generative AI

Lecture 2: Generative AI Provider Breach

Lecture 3: How Threat Actors Evolve with AI Technologies

Chapter 3: Specific Attack Vectors and Vulnerabilities

Lecture 1: Specific Attack Vectors and Vulnerabilities

Lecture 2: Prompt Injections

Lecture 3: Indirect Prompt Injection

Lecture 4: The importance of Proper Sandboxing in AI Environments

Lecture 5: Addressing the Issue of AI hallucinations or False Outputs

Chapter 4: Network-Level Risks and AI Specific Attacks

Lecture 1: Server Side Request Forgery (SSRF)

Lecture 2: DDoS Attacks

Lecture 3: Data Poisoning

Lecture 4: Model Bias

Chapter 5: Legal and Ethical Considerations

Lecture 1: Copyright Violations

Lecture 2: Ethical AI Use

Chapter 6: Conclusion

Lecture 1: Conclusion

Instructors

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  • 5 stars: 4 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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