Cybersecurity and Artificial Intelligence of Things (AIoT) in Education: Enhancing Security in Smart Learning Environment
DOI:
https://doi.org/10.53819/81018102t5429Abstract
Cybersecurity (CS), Artificial Intelligence (AI), and the Internet of Things (IoT) are revolutionizing education by enabling adaptive learning systems and smart educational tools. The integration of AI and IoT, known as Artificial Intelligence of Things (AIoT), offers transformative possibilities but also introduces significant cybersecurity risks. Protecting AIoT-enabled devices and systems is essential to ensure secure and efficient educational environments. This research aims to address cybersecurity challenges in AIoT-enabled educational tools and adaptive learning systems. It investigates user security behaviours, evaluates threats, and compares the effectiveness of AIoT-based and traditional cybersecurity approaches. The study utilized a mixed-methods approach, collecting data by qualitative analysis of archival data, opinion & guidelines of industrial experts and via online and offline surveys of 10,024 educational participants around the globe to understand the relationship between user behaviours and cybersecurity threats in education. A machine learning-based AI model was developed to detect anomalies with high precision, and case studies were conducted to analyse real-world cybersecurity scenarios in educational contexts. The study proposed a Cyber-AIoT Solution for a Smart Learning Environment (SLE). The results demonstrated that the AI model effectively mitigates cybersecurity threats, ensuring intelligent mobility and secure operations within educational systems. The findings highlight the applicability of AIoT in creating robust and secure educational ecosystems. The research emphasizes the importance of safeguarding AIoT-enabled tools in education, providing a practical framework to address vulnerabilities and enhance security in smart learning environments. Future work should focus on developing globally scalable cybersecurity solutions, enhancing AI-driven threat detection, and fostering collaboration among educational institutions and technology providers to build secure and resilient smart Learning systems.
Keywords: Cybersecurity, Artificial Intelligence of Things, Education, Security, Smart Learning Environment
References
Abichandani, P., Sivakumar, V., Lobo, D., Iaboni, C., & Shekhar, P. (2022). Internet of things curriculum, pedagogy, and assessment for stem education A review of literature. IEEE Access, 10, 38351–38369. https://ieeexplore.ieee.org/abstract/document/9749084
Aloul, F.A., The need for effective information security awareness. Journal of advances in information technology, 2012. 3(3) p. 176-183. https://doi.org/10.4304/jait.3.3.176-183
Arsenio A, H. Serra, R. Francisco, F. Nabais, J. Andrade, E. Serrano, Internet of intelligent things Bringing artificial intelligence into things and communication networks, in Interco operative Collective Intelligence Techniques and Applications, Springer, 2014, pp. 1–37. https://doi.org/10.1007/978-3-642-35016-0_1
Baidoo Anu, L. Owusu Ansah, Education in the era of generative artificial intelligence (AI) Understanding the potential benefits of ChatGPT in promoting teaching and learning, 2023, Available at SSRN 4337484. https://doi.org/10.2139/ssrn.4337484
Bajaj, V. Sharma, Smart Education with artificial intelligence-based determination of learning styles, Procedia Compute. Sci. 132 (2018) 834–842. https://doi.org/10.1016/j.procs.2018.05.095
Blokland, P., Reniers, G., 2019. An ontological and semantic foundation for safety and security science. Sustainability 11 (21), 6024. https//doi.org/10.3390/ su11216024
Casteel, C., Peek-Asa, C., 2000. Effectiveness of crime prevention through environmental design (CPTED) in reducing robberies. Am. J. Prev. Med. 18 (4), 99–115. https://doi. org/10.1016/s0749-3797(00)00146-x.
Chakraborty P, Dizon-Paradis RN, Bhunia S (2022) ARTS a framework for AI-rooted IoT system design automation. IEEE Embed Syst Lett 14(3)151–154.
Chałubinska-Jentkiewicz, K. (2021). Access to the ICT network as a public task of local government. Lex Localis, 19 (1), 175–195.10.4335/19.1.175-195(2021).
Chinju Paul and Amal Ganesh C. Sunitha, "An IoT-Based Smart Classroom", Lecture Notes on Data Engineering and Communications Technologies, vol. 15, pp. 9-14, Sept 2018. https://doi.org/10.1007/978-981-10-8681-6_2
Cohen, J., 2021. School safety and violence research and clinical understandings, trends, and improvement strategies. Int. J. Appl. Psychoanal. Stud. 18 (3), 252–263. https//doi.org/10.1002/aps.1718.
Hilgurt SY. 2022. Pattern handling for quantifying hardware components of signature-based cybersecurity systems.
Huang, L. S., Su, J. Y., & Pao, T. L. (2019). A context aware smart classroom architecture for smart campuses. Applied Sciences, 9(9), 1837. https://doi.org/10.3390/app9091837
Jalali, M.S., M. Siegel, and S. Madnick, Decision-making and biases in cybersecurity capability development Evidence from a simulation game experiment. The Journal of Strategic Information Systems, 2019. 28(1) p. 66-82. https://doi.org/10.1016/j.jsis.2018.09.003
Kesan & Zhang, (2019) An empirical investigation of the relationship between local government budgets, IT expenditures, and cyber losses 20
Kumar V, Sinha D. 2022. Hybrid approach using deep autoencoder and machine learning techniques for cyber-attack detection. International Journal of Ambient Computing and Intelligence 13(1)1-21 https://doi.org/10.4018/IJACI.293098
Lahat, T. Adali and Jutten, "Multimodal Data Fusion an Overview of Methods Challenges and Prospects", Proceedings of the IEEE, vol. 103, pp. 1449-1477, Sept 2015. https://doi.org/10.1109/JPROC.2015.2460697
Lamoreaux, D., Sulkowski, M.L., 2019. An alternative to fortified schools Using crime prevention through environmental design (CPTED) to balance student safety and psychological well-being. Psychol. Sch. 57 (1), 152–165. https//doi.org/10.1002/ pits.22301
Liu, S., Chen, Y., Huang, H., Xiao, L., & Hei, X. (2018). Towards smart educational recommendations with reinforcement learning in classroom. In 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (pp. 1079–1084). https://doi.org/10.1109/TALE.2018.8615217
Liu, Y., Zhang, P., & Zhou, J. (2018). Using AI to enhance the security of Internet of Things. Sensors, 18(2), 403.
Maurseth, P.B., The effect of the Internet on economic growth Counter-evidence from cross-country panel data. Economics Letters, 2018. 172 p. 74-77. https://doi.org/10.1016/j.econlet.2018.08.034
Mircea, M., Stoica, M., & Ghilic-Micu, B. (2021). Investigating the impact of the internet of things in higher education environment. IEEE Access, 9, 33396–33409. https://doi.org/10.1109/ACCESS.2021.3060964
Norris, D. (2021). A new look at local government cybersecurity in 2020. Public Management (PM), 103 (7), 15–20. https//www.proquest.com/docview/ 2561966386?accountid = 13380&forcedol = true
Olawale OP, Ebadinezhad S. 2023. The detection of abnormal behavior in healthcare IoT using IDS, CNN, and SVM. In: Lecture Notes on Data Engineering and Communications Technologies. Cham: Springer. https://doi.org/10.1007/978-981-99-0835-6_27
Qin, M., Hu, W., Qi, X., & Chang, T. (2024). Do the benefits outweigh the disadvantages? Exploring the role of artificial intelligence in renewable energy. Energy Economics, 131, Article 107403. https://doi.org/10.1016/j.eneco.2024.107403
Robert, C. DicksonDeane, C. Guevara, L. Koster, M. SanchezMendiola, N. Arbino, w. AlFreih, L. Skallerup Bessette, J. Stine, Pelletier, M. McCormack, J. Reeves, 2022 EDUCAUSE Horizon Report Teaching and Learning Edition, Technical Report, EDUCAUSE, 2022.
Sharvari Ravindran, Saptarshi Chaudhuri, Jyotsna Bapat, Debabrata Das (2024) Novel adaptive multi-user multi-services scheduling to enhance throughput in 5G-advanced and beyond IEEE Transactions on Network and Service Management. https://doi.org/10.1109/TNSM.2024.3351669
Singh, A.P. (.2023). AI in Cyber Security Advantages, Applications and Use Cases. Retrieved from https//www.analyticsvidhya.com/blog/2023/02/future-of-ai-an d-machine-learning-in-cybersecurity/.
Tsai, W.-T. (2022). Cloud-based virtual laboratory for network security education. IEEE Transactions on Education, 57(3), 145–150. https://doi.org/10.1109/TE.2013.2282285
Xu, W. Yu, D. Griffith, and N. Golmie, ‘‘A survey on industrial Internet of Things: A cyber-physical systems perspective,’’ IEEE Access, vol. 6, pp. 78238–78259, 2018. R. https://doi.org/10.1109/ACCESS.2018.2884906
Zhang, J., Wang, Y., Li, S., & Shi, S. (2021). An architecture for IoT-enabled smart transportation security system: A geospatial approach. IEEE Internet of Things Journal, 8(8), 6205–6213. https://doi.org/10.1109/JIOT.2020.3041386
Zhang, Q., Wang, K., & Zhou, S. (2020). Application and practice of vr virtual education platform in improving the quality and ability of college students. IEEE Access, 8, 162830–162837. https://doi.org/10.1109/ACCESS.2020.3019262
Zhang, X.; Chen, Y.; Hu, L.; Wang, Y. The metaverse in education Definition, framework, features, potential applications, challenges, and future research topics. Front. Psychol. 2022, 13, 108233. https://doi.org/10.3389/fpsyg.2022.1016300
Zhang-Kennedy, L. and S. Chiasson, A systematic review of multimedia tools for cybersecurity awareness and education. ACM Computing Surveys (CSUR), 2021. 54(1) p. 1 39. https://doi.org/10.1145/3427920
