Development of a Laboratory Platform for UAV Cybersecurity Education
- Conference
- Location
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Virtual Conference
- Publication Date
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July 26, 2021
- Start Date
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July 26, 2021
- End Date
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July 19, 2022
- Conference Session
- Tagged Division
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Electrical and Computer
- Page Count
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9
- DOI
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10.18260/1-2--36958
- Permanent URL
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https://peer.asee.org/36958
- Download Count
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482
Paper Authors
Yushan Jiang Embry-Riddle Aeronautical University
Yushan Jiang is a Ph.D. student in the Department of Electrical Engineering and Computer Science, Embry-Riddle Aeronautical University (ERAU), Daytona Beach, Florida. He is a graduate research assistant in the Security and Optimization for Networked Globe Laboratory (SONG Lab). His research interests include cybersecurity, unmanned aircraft system, machine learning, and Internet of Things.
Jiawei Yuan University of Massachusetts Dartmouth
Lulu Sun Embry-Riddle Aeronautical University
Lulu Sun is a professor in the Engineering Fundamentals Department at Embry-Riddle Aeronautical University, where she has taught since 2006. She received her Ph.D. degree in Mechanical Engineering from University of California, Riverside, in 2006. Before joining Embry-riddle, she worked in the consulting firm of Arup at Los Angeles office as a fire engineer. Her research interests include second language acquisition in programming languages, flipped classroom, and virtual training. She is a member of the American Society for Engineering Education (ASEE), and a member of the Air Traffic Control Association (ATCA).
Houbing Herbert Song Embry-Riddle Aeronautical University
Houbing Song (M’12–SM’14) received the Ph.D. degree in electrical engineering from the University of Virginia, Charlottesville, VA, in August 2012, and the M.S. degree in civil engineering from the University of Texas, El Paso, TX, in December 2006.
In August 2017, he joined the Department of Electrical Engineering and Computer Science, Embry-Riddle Aeronautical University, Daytona Beach, FL, where he is currently an Assistant Professor and the Director of the Security and Optimization for Networked Globe Laboratory (SONG Lab, www.SONGLab.us). He served on the faculty of West Virginia University from August 2012 to August 2017. In 2007 he was an Engineering Research Associate with the Texas A&M Transportation Institute. He has served as an Associate Technical Editor for IEEE Communications Magazine (2017-present), an Associate Editor for IEEE Internet of Things Journal (2020-present) and IEEE Journal on Miniaturization for Air and Space Systems (J-MASS) (2020-present), and a Guest Editor for IEEE Journal on Selected Areas in Communications (J-SAC), IEEE Internet of Things Journal, IEEE Transactions on Industrial Informatics, IEEE Sensors Journal, IEEE Transactions on Intelligent Transportation Systems, and IEEE Network. He is the editor of six books, including Big Data Analytics for Cyber-Physical Systems: Machine Learning for the Internet of Things, Elsevier, 2019, Smart Cities: Foundations, Principles and Applications, Hoboken, NJ: Wiley, 2017, Security and Privacy in Cyber-Physical Systems: Foundations, Principles and Applications, Chichester, UK: Wiley-IEEE Press, 2017, Cyber-Physical Systems: Foundations, Principles and Applications, Boston, MA: Academic Press, 2016, and Industrial Internet of Things: Cybermanufacturing Systems, Cham, Switzerland: Springer, 2016. He is the author of more than 100 articles. His research interests include cyber-physical systems, cybersecurity and privacy, internet of things, edge computing, AI/machine learning, big data analytics, unmanned aircraft systems, connected vehicle, smart and connected health, and wireless communications and networking. His research has been featured by popular news media outlets, including IEEE GlobalSpec's Engineering360, USA Today, U.S. News & World Report, Fox News, Association for Unmanned Vehicle Systems International (AUVSI), Forbes, WFTV, and New Atlas.
Dr. Song is a senior member of ACM and an ACM Distinguished Speaker. Dr. Song was a recipient of the Best Paper Award from the 12th IEEE International Conference on Cyber, Physical and Social Computing (CPSCom-2019), the Best Paper Award from the 2nd IEEE International Conference on Industrial Internet (ICII 2019), the Best Paper Award from the 19th Integrated Communication, Navigation and Surveillance technologies (ICNS 2019) Conference, the Best Paper Award from the 6th IEEE International Conference on Cloud and Big Data Computing (CBDCom 2020), and the Best Paper Award from the 15th International Conference on Wireless Algorithms, Systems, and Applications (WASA 2020).
Abstract
There is an increasing need to fly unmanned aerial vehicles (UAVs) to enable a wide variety of beneficial applications such as emergency/disaster response, observation and study of weather phenomena including severe storms. However, UAVs are subject to cybersecurity threats stemming from increasing reliance on computer and communication technologies. There is a need to foster a robust workforce with integrated UAV and cybersecurity competencies. In addition to technique challenges, current UAV cybersecurity education also faces two significant non-technical challenges: first, there are federal or state rules and regulations on UAV flights; second, the number of designated UAV test sites is limited. A three years NSF SaTC funded project in 2020 will specifically address these challenges. We propose to develop a laboratory platform for UAV cybersecurity education. To be specific, our platform integrates software simulation with hardware-in-the-loop (HIL) simulation to simulate different UAV scenarios, on the top of which cybersecurity components are developed for hands-on practicing. We use a firmware for UAV system development, Pixhawk with related open-source software packages, as the basic simulation framework. On the top of the simulation environment, a series of hands-on exercise modules will be developed to cover UAV cybersecurity issues. Motivated by different types of cybersecurity threats to UAVs, we will adopt the scenario based design and set up several categories of exercise modules including common threats in UAV and additional modules for newly identified threats with corresponding actors, goals, actions, and events. In such a manner offense and defense tasks can be further developed. The proposed platform has the potential to be adopted by universities with limited resources to UAV cybersecurity. It will help educate future workforce with integrated UAV and cybersecurity competencies, towards secure and trustworthy cyberspace around UAVs.
Jiang, Y., & Yuan, J., & Sun, L., & Song, H. H. (2021, July), Development of a Laboratory Platform for UAV Cybersecurity Education Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36958
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