Generative AI Cybersecurity & Privacy for Leaders: A Primer
Protect data with generative AI by addressing threats like prompt injection, deepfakes, and AI phishing for responsible implementation.
Protect data with generative AI by addressing threats like prompt injection, deepfakes, and AI phishing for responsible implementation.
This comprehensive primer provides an essential foundation in generative AI cybersecurity and privacy for organizational leaders. The course explores the transformative potential of AI while addressing the specific risks it introduces to enterprise security. You'll learn to safeguard organizational privacy by understanding the implications of AI systems and the risks posed by data fusion across platforms. The course covers emerging AI-specific threats, helping you develop a clear understanding of vulnerabilities like prompt injection, deepfakes, AI-enhanced phishing, and adversarial text in AI deployments. You'll gain the foundational tools and techniques to implement secure environments for AI development and responsible usage. Designed for cybersecurity and privacy leaders, IT professionals, business executives, and policy makers, this course balances innovation with protection. By the end, you'll be empowered to lead AI initiatives that drive progress while effectively mitigating the unique cybersecurity risks posed by generative AI.
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What you'll learn
Safeguard organizational privacy by understanding AI data risks and fusion challenges
Identify and mitigate emerging AI-specific threats like prompt injection and adversarial text
Develop strategies to protect against deepfakes and AI-generated misinformation
Recognize how AI enables hyper-personalized phishing and implement defensive measures
Implement enterprise-level information access controls for secure AI adoption
Skills you'll gain
This course includes:
2 Hours PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This course provides essential knowledge for leaders navigating the complex intersection of generative AI, cybersecurity, and privacy. It begins with an individual perspective on data protection when using AI systems, then explores security vulnerabilities specific to generative AI including prompt injection attacks and adversarial text. Students learn about the growing threat of deepfakes and misinformation, followed by the challenges of AI-powered hyper-personalization in phishing and persuasion. The final module shifts to an organizational perspective, covering information access control, preventing accidental data leakage, and best practices for responsible AI adoption that maintains privacy and security in enterprise environments.
Generative AI Privacy & Security: An Individual Perspective
Module 1 · 56 Minutes to complete
Generative AI Security & Prompting
Module 2 · 27 Minutes to complete
Misinformation & Deepfakes
Module 3 · 51 Minutes to complete
Hyper-Personalization, Persuasion, & Phishing
Module 4 · 57 Minutes to complete
Generative AI Privacy & Security: A Perspective for Businesses & Organizations
Module 5 · 42 Minutes to complete
Fee Structure
Instructors
Professor of Computer Science at Vanderbilt University
Dr. Jules White is a Professor of Computer Science at Vanderbilt University, where he also serves as the Director of the Initiative on the Future of Learning & Generative AI and the Associate Dean of Strategic Learning Programs in the School of Engineering. He is recognized for creating one of the first online courses in Prompt Engineering, which focuses on effective communication with AI systems. A recipient of the National Science Foundation CAREER Award, Dr. White has published over 160 papers and has received multiple Best Paper Awards for his research. His work primarily explores large language models, including ChatGPT, as well as topics in cybersecurity and software engineering across various sectors such as healthcare and manufacturing. He leads the Mobile Application Computing, Optimization, and Security Methods (MAGNUM) Group at Vanderbilt University, where he conducts his research and development efforts.
Instructor at Vanderbilt University specializing in AI-powered cybersecurity
Dr. Sam Hays is an instructor at Vanderbilt University, focusing on the intersection of artificial intelligence and cybersecurity. He currently teaches two online courses: "ChatGPT + Cybersecurity: AI-Powered Tabletops & Training" and "Generative AI Cybersecurity & Privacy for Leaders: A Primer". These courses are part of the Generative AI Cybersecurity & Privacy for Leaders Specialization, which aims to equip leaders with the knowledge and tools to address the unique cybersecurity risks introduced by AI while harnessing its potential to strengthen cybersecurity planning and response. Dr. Hays' courses cover critical topics such as using ChatGPT to enhance cybersecurity tabletop exercises, understanding AI-specific security threats, and implementing strategies to improve organizational preparedness against evolving cybersecurity challenges. His work contributes to Vanderbilt University's broader initiatives in the rapidly evolving field of generative artificial intelligence, positioning the institution as a leader in shaping the future of this transformative technology.
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