Coalescing Research into Modular and Safe Educational Cybersecurity Labs with AI Solutions

Driven by a cybercrime industry worth over $6 trillion, the demand for cybersecurity professionals is surging with a projected increase of over 35% in jobs over the next decade according to the US Department of Labor's BLS. Simultaneously, advancements in Artificial Intelligence (AI), Data Science (DS), and Machine Learning (ML) are reshaping industries and cre-ating challenges, notably job displacement for the under-skilled. This research-to-practice full paper addresses the critical need to integrate AI/DS/ML into cybersecurity education to meet these evolving demands. We envision a marriage of AI/DS/ML and cybersecurity (ADM4CYB) through a research-to-education paradigm. Despite extensive research, there remains a significant lack of publicly accessible labs that apply AI, DS, and ML to real-world cyber-security challenges. As such, readily available, easy to adopt, modular, and hands-on labs applying AI/DS/ML solutions to cybersecurity problems are highly desirable. At this juncture, we are developing a methodology that enables instructors and researchers to transform their work into practical, safe, and interactive teaching labs, enhancing student learning across various cybersecurity topics. Our initiative aims to integrate AI, DS, and ML techniques into interactive labs to effectively address current cybersecurity challenges. These modular labs provide students with both theoretical knowledge and hands-on experience, essential for adapting to the rapidly evolving field. By creating accessible labs, our methodology empowers students to develop skills across various cybersecurity topics. We also report results of our preliminary evaluation after using the first lab from this methodology in two classes that show increased learning, heightened levels of interest and motivation in the fields of networking, cybersecurity, AI/DS/ML, as well as coding.