Clint Bodungen is a globally recognized cybersecurity professional and thought leader with over 25 years of experience (of which 20 years have been focused on ICS/OT cybersecurity). His journey in cybersecurity began at the age of eleven when he started programming on a Tandy 1200, and since then, his career has been nothing short of remarkable. A veteran of the United States Air Force, Clint has established himself as a prominent figure in the field, having worked for notable cybersecurity firms like Symantec, Industrial Defender, Booz Allen Hamilton, and Kaspersky Lab. His expertise extends to the impact of AI on cybersecurity, and he has played a pivotal role in addressing the industry's training and education gaps. Clint is renowned for his innovative approaches and has contributed to the field as the author of two books: the best seller, "Hacking Exposed: Industrial Control Systems," and the upcoming "ChatGPT for Cybersecurity Cookbook." He has written an array of articles, technical papers, and training courses, with a primary focus on cybersecurity vulnerability assessment, penetration testing/red teaming, and risk management. Even before the public emergence of generative AI and large language models (LLM), he had already developed a variety of cybersecurity tools and apps that leverage this technology. Over the past decade, Clint has been at the forefront of integrating gamification and AI applications into cybersecurity training. His dedication and innovation culminated in the creation of ThreatGEN® Red vs. Blue, the world's first online multiplayer cybersecurity game crafted to impart real-world cybersecurity skills. This flagship product marks Clint's foray as a pioneer in cybersecurity gamification, a testament to his progressive vision. Clint's enduring passion and goal are to redefine industry standards for cybersecurity education using computer gaming (gamification) and AI technology to present a revolutionary, engaging approach to this essential field, and set new precedents for effective and interactive learning.
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