2025 ASEE Annual Conference & Exposition

BOARD #108: DARE-AI: Discovery, Analysis, Research and Exploration Based Experiential Learning Platform for Teaching Integrated AI and Cybersecurity

Presented at Computing and Information Technology Division (CIT) Poster Session

Machine learning (ML) algorithms and artificial intelligence (AI) systems have already had an immense impact on our society. Lately, AI/ML has shown to be able to create machine cognition comparable to or even better than human cognition for some applications. For emerging applications, AI is also regarded to provide cybersecurity solutions (i.e., AI for cybersecurity) by detecting anomalies, adapting security parameters based on ongoing cyberattacks, and reacting in real-time to combat cyber-adversaries. However, ML algorithms and AI systems are vulnerable to manipulation of data or learning models, biases, and low credible information due to flaws in learning models and input data. Therefore, ML algorithms and AI systems need robust security and correctness (i.e., cybersecurity for AI) to permit fair and trustworthy AI systems. Unfortunately, AI and cybersecurity have traditionally been treated as separate fields, with little emphasis on their intersection in education. The primary goal of this paper is to discover, explore, develop and integrate a scalable instructional approach for integrated AI and cybersecurity (DARE-AI for short) in undergraduate and graduate curricula. This is accomplished by creating a “learning by doing” approach to address emerging AI and cybersecurity issues that are not covered in an integrated way, if at all, in traditional curricula. The experiments are designed to study fair and trustworthy AI, adaptive intrusion detection, online learning, federated learning, distributed learning, and adversarial learning. We present learning outcomes and results using surveys and assessments. The developed DARE-AI modules help train the next-generation STEM workforce with knowledge of integrated cybersecurity and AI that is expected to help not only to meet evolving demands of the US government and industries, but also to improve the nation’s economic security and preparedness.

Authors

Utsab Khakurel Howard University [biography]

Utsab Khakurel is a Ph.D. candidate in the Department of Electrical Engineering and Computer Science (EECS) at Howard University, Washington, DC, USA, under the supervision of Dr. Danda B Rawat. Contact him at utsab.khakurel@bison.howard.edu.
Prof. Danda B Rawat http://orcid.org/0000-0003-3638-3464 Howard University [biography]

Dr. Danda B. Rawat is an Associate Dean for Research & Graduate Studies, a Full Professor in the Department of Electrical Engineering & Computer Science (EECS), Founding Director of the Howard University Data Science & Cybersecurity Center, Founding Director of DoD Center of Excellence in Artificial Intelligence & Machine Learning (CoE-AIML), Director of Cyber-security and Wireless Networking Innovations (CWiNs) Research Lab, and Director of Graduate Cybersecurity Certificate Program at Howard University, Washington, DC, USA. Dr. Danda B. Rawat successfully led and established the Research Institute for Tactical Autonomy (RITA), the 15th University Affiliated Research Center (UARC) of the US Department of Defense as the PI/Founding Executive Director at Howard University, Washington, DC, USA. Dr. Rawat is engaged in research and teaching in the areas of cybersecurity, machine learning, big data analytics and wireless networking for emerging networked systems including cyber-physical systems (eHealth, energy, transportation), Internet-of-Things, multi domain operations, smart cities, software defined systems and vehicular networks. Dr. Rawat has secured over $110 million as a PI and over $18 million as a Co-PI in research funding from the US National Science Foundation (NSF), US Department of Homeland Security (DHS), US National Security Agency (NSA), US Department of Energy, National Nuclear Security Administration (NNSA), National Institute of Health (NIH), US Department of Defense (DoD) and DoD Research Labs, Industry (Microsoft, Intel, VMware, PayPal, Mastercard, Meta, BAE, Raytheon etc.) and private Foundations. Dr. Rawat is the recipient of the US NSF CAREER Award, the US Department of Homeland Security (DHS) Scientific Leadership Award, Presidents’ Medal of Achievement Award (2023) at Howard University, Provost's Distinguished Service Award 2021, Researcher Exemplar Award 2019 and Graduate Faculty Exemplar Award 2019 from Howard University, the US Air Force Research Laboratory (AFRL) Summer Faculty Visiting Fellowship 2017, Outstanding Research Faculty Award (Award for Excellence in Scholarly Activity) at GSU in 2015, the Best Paper Awards (IEEE CCNC, IEEE ICII, IEEE DroneCom and BWCA) and Outstanding PhD Researcher Award in 2009. He has delivered over 100 Keynotes and invited speeches at international conferences and workshops. Dr. Rawat has published over 350 scientific/technical articles and 11 books. Dr. Rawat has successfully supervised and graduated 35 PhD students (out of which 28 were under-represented PhD students including 13 female PhD students), successfully supervised 30+ MS students and mentored 7 postdocs, and has been supervising 25 PhD students and mentoring 3 postdocs. Furthermore, he has successfully mentored over 120 minority undergraduate students. He has been serving as an Editor/Guest Editor for over 100 international journals including the Associate Editor of IEEE Transactions on Big Data, Associate Editor of IEEE Transactions on Information Forensics & Security, Associate Editor of Transactions on Cognitive Communications and Networking, Associate Editor of IEEE Transactions of Service Computing, Editor of IEEE Internet of Things Journal, Editor of IEEE Communications Letters, Associate Editor of IEEE Transactions of Network Science and Engineering and Technical Editors of IEEE Network, and Associate Editor of ACM Transactions on Intelligent Systems and Technology. He has been in Organizing Committees for several IEEE flagship conferences such as IEEE INFOCOM, IEEE CNS, IEEE ICC, IEEE GLOBECOM and so on. He served as a technical program committee (TPC) member for several international conferences including IEEE INFOCOM, IEEE GLOBECOM, IEEE CCNC, IEEE GreenCom, IEEE ICC, IEEE WCNC and IEEE VTC conferences. He served as a Vice Chair of the Executive Committee of the IEEE Savannah Section from 2013 to 2017. Dr. Rawat received the Ph.D. degree from Old Dominion University, Norfolk, Virginia. Dr. Rawat served as a Graduate Program Director of Howard Computer Science Graduate Programs (2017 - 2025). Dr. Rawat is a Senior Member of IEEE and a Lifetime Professional Senior Member of ACM, a Lifetime Member of Association for the Advancement of Artificial Intelligence (AAAI), a Champion Member of USENIX (The Advanced Computing Systems Association), a lifetime member of SPIE, a member of ASEE, a member of AAAS, a member of SAE International, and a Fellow of the Institution of Engineering and Technology (IET). He is an ACM Distinguished Speaker and an IEEE Distinguished Lecturer (FNTC and VTS).

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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