Overview

This course provides a comprehensive understanding of Generative AI (GenAI) technologies, their applications across various industries, and the associated security and ethical considerations. Participants will gain insights into the types of Generative AI models, their potential vulnerabilities, and practical strategies for mitigating risks. Through detailed lectures, real-world examples, and case studies, this course aims to equip professionals with the knowledge and tools necessary to promote secure and ethical use of Generative AI.Security is a major concern in the deployment of Generative AI, and this course will delve into specific threats such as data poisoning, prompt injection attacks, model inversion, data leakage, and model stealing. Through detailed examples from different industries, participants will learn to identify and mitigate these risks. Ethical concerns, including bias in AI-generated content, will also be addressed, providing guidelines for ethical AI use.Participants will explore real-world case studies to understand the practical implications of these risks and learn to develop a comprehensive security framework tailored to their organizational needs. The course will emphasize best practices for the safe use of Generative AI, including the importance of sandboxing to prevent malicious code execution and promoting a culture of security awareness within organizations.By the end of the course, participants will be equipped with the knowledge and tools necessary to ensure the secure and ethical deployment of Generative AI technologies. Key Areas Covered Are:Applications of Generative Al in various industriesSecurity Risks Associated with Generative AlEthical Concerns and Bias in Al-Generated ContentData Poisoning and Prompt Injection AttacksExample of Data Poisoning in different IndustriesExample of Prompt Injection Attacks in diferent IndustriesModel Inversion and Data LeakageExample of Model Inversion in different IndustriesExample of Data Leakage in different IndustriesModel Stealing and Its ImplicationsExample of Model Stealing in different IndustriesHallucinations in Generative AlInadequate Sandboxing and Malicious Code ExecutionExample of Inadequate Sandboxing in different IndustriesExample of Malicious Code in different IndustriesTop Threats Presented by Public Alcase studiescreating six steps security framework Best Practices for Safe Use of Generative Al Promoting a Culture of Security Awareness in AlLearning Outcomes:By the end of this course, participants will:Understand the fundamental concepts and types of Generative AI models.Recognize the diverse applications of Generative AI across various industries.Identify security risks and ethical concerns associated with Generative AI.Implement best practices for mitigating security threats and promoting ethical AI use.Develop a comprehensive security framework tailored to their organizational needs.Foster a culture of security awareness and responsibility in AI development and deployment.

Skills

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