Artificial Intelligence Assistants in Digital Learning Environments and Cybersecurity Challenges
DOI:
https://doi.org/10.31861/sisiot2026.1.01001Keywords:
AI assistants, digital learning environments, cybersecurity, data encryption, intrusion detectionAbstract
Integration of Artificial Intelligence (AI) Assistants into digital learning environments is becoming an essential part of modern educational processes. The use of AI assistants enables personalized learning that takes into account the individual needs of students, enhances communication efficiency between students and instructors, and automates routine administrative tasks. As a result, students gain access to adaptive learning materials, timely support, and valuable educational resources, significantly improving their learning experience and outcomes. This approach fosters deeper student engagement in the learning process, making education more interactive and convenient for all participants. However, the implementation of AI assistants in educational processes is accompanied by numerous cybersecurity challenges, particularly concerning data privacy protection. The article provides an in-depth examination of the risks associated with using AI technologies in learning environments. It analyzes existing technological and organizational approaches to minimizing these risks. Technological approaches include the use of advanced data encryption methods, multi-factor authentication, intrusion detection and prevention systems (IDS/IPS), and regular security audits. These measures are aimed at enhancing the protection of AI systems from potential cyberattacks and reducing the risk of data compromise. Organizational approaches involve developing security policies for users, conducting training sessions on cyber hygiene, and regularly informing them about current cyber threats. This helps foster a culture of cybersecurity among students and educators, reducing the likelihood of successful social engineering attacks. The article emphasizes the need for developing comprehensive cybersecurity strategies that consider the specific operations of AI assistants. Implementing such strategies is critically important for creating a secure digital learning environment where AI technologies are used. The proposed approaches can serve as a foundation for developing effective data protection strategies and promoting the safe integration of innovative technologies into digital learning environments.
Downloads
References
E. Dimitriadou and A. Lanitis, “A critical evaluation, challenges, and future perspectives of using artificial intelligence and emerging technologies in smart classrooms,” Smart Learn. Environ., vol. 10, no. 1, p. 12, 2023, doi: 10.1186/s40561-023-00231-3.
A. Alam, “Employing adaptive learning and intelligent tutoring robots for virtual classrooms and smart campuses: Reforming education in the age of artificial intelligence,” in R. N. Shaw, S. Das, V. Piuri, and M. Bianchini, Eds., Adv. Comput. Intell. Technol., Lecture Notes in Electrical Engineering, vol. 914. Singapore: Springer, 2022, pp. 395–406, doi: 10.1007/978-981-19-2980-9_32.
B. Cope, M. Kalantzis, and D. Searsmith, “Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies,” Educ. Philos. Theory, vol. 53, no. 12, pp. 1229–1245, 2021, doi: 10.1080/00131857.2020.1728732.
V. Kuleto et al., “Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions,” Sustainability, vol. 13, no. 18, p. 10424, 2021, doi: 10.3390/su131810424.
M. Hooda, C. Rana, O. Dahiya, A. Rizwan, and M. S. Hossain, “Artificial intelligence for assessment and feedback to enhance student success in higher education,” Math. Problems Eng., vol. 2022, no. 1, p. 5215722, 2022, doi: 10.1155/2022/5215722.
A. Alam, “Possibilities and Apprehensions in the Landscape of Artificial Intelligence in Education,” in Proc. 2021 Int. Conf. Comput. Intell. Comput. Appl. (ICCICA), Nagpur, India, 2021, pp. 1–8, doi: 10.1109/ICCICA52458.2021.9697272.
A. Maedche et al., “AI-based digital assistants: Opportunities, threats, and research perspectives,” Bus. Inf. Syst. Eng., vol. 61, no. 4, pp. 535–544, 2019, doi: 10.1007/s12599-019-00600-8.
M. L. Owoc, A. Sawicka, and P. Weichbroth, “Artificial intelligence technologies in education: Benefits, challenges and strategies of implementation,” in M. L. Owoc and M. Pondel, Eds., Artif. Intell. Knowl. Manage., IFIP Advances in Information and Communication Technology, vol. 599, Cham, Switzerland: Springer, 2021, pp. 37–58, doi: 10.1007/978-3-030-85001-2_4.
S. F. Ahmad, M. M. Alam, M. K. Rahmat, M. S. Mubarik, and S. I. Hyder, “Academic and administrative role of artificial intelligence in education,” Sustainability, vol. 14, no. 3, p. 1101, 2022, doi: 10.3390/su14031101.
G. J. Hwang, H. Xie, B. W. Wah, and D. Gašević, “Vision, challenges, roles and research issues of Artificial Intelligence in Education,” Comput. Educ.: Artif. Intell., vol. 1, p. 100001, 2020, doi: 10.1016/j.caeai.2020.100001.
W. Holmes, J. Persson, I. A. Chounta, B. Wasson, and V. Dimitrova, Artificial Intelligence and Education: A Critical View Through the Lens of Human Rights, Democracy and the Rule of Law. Strasbourg, France: Council of Europe, 2022, ISBN 978-92-871-9236-3.
A. Aldoseri, K. N. Al-Khalifa, and A. M. Hamouda, “Re-thinking data strategy and integration for artificial intelligence: Concepts, opportunities, and challenges,” Appl. Sci., vol. 13, no. 12, p. 7082, 2023, doi: 10.3390/app13127082.
M. Decuypere, E. Grimaldi, and P. Landri, “Introduction: Critical studies of digital education platforms,” Crit. Stud. Educ., vol. 62, no. 1, pp. 1–16, 2021, doi: 10.1080/17508487.2020.1866050.
Y. Chen, S. Jensen, L. J. Albert, S. Gupta, and T. Lee, “Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success,” Inf. Syst. Front., vol. 25, no. 1, pp. 161–182, 2023, doi: 10.1007/s10796-022-10291-4.
R. Reyes, D. Garza, L. Garrido, V. De la Cueva, and J. Ramirez, “Methodology for the implementation of virtual assistants for education using Google Dialogflow,” in L. Martínez-Villaseñor, I. Batyrshin, and A. Marín-Hernández, Eds., Advances in Soft Computing (MICAI 2019), Lecture Notes in Computer Science, vol. 11835, Cham, Switzerland: Springer, 2019, pp. 440–451, doi: 10.1007/978-3-030-33749-0_35.
I. Rozlomii, N. Yehorchenkova, A. Yarmilko, and S. Naumenko, “Data protection in the utilization of natural language processors for trend analysis and public opinion: Cryptographic aspect,” in Proc. 2nd Int. Workshop Social Commun. Inf. Act. Digit. Humanities (SCIA-2023), Lviv, Ukraine, 2023, pp. 1–11, doi: 10.5281/zenodo.21131868.
T. Kabudi, I. Pappas, and D. H. Olsen, “AI-enabled adaptive learning systems: A systematic mapping of the literature,” Comput. Educ.: Artif. Intell., vol. 2, p. 100017, 2021, doi: 10.1016/j.caeai.2021.100017.
K. M. Fuad, “Organizational intelligence in digital innovation: Evidence from Georgia State University,” Ph.D. dissertation, Georgia State Univ., Georgia, USA, 2022, doi: 10.31922/Z1BC-1A51.
S. Dutta, S. Ranjan, S. Mishra, V. Sharma, P. Hewage, and C. Iwendi, “Enhancing educational adaptability: A review and analysis of AI-driven adaptive learning platforms,” in Proc. 2024 4th Int. Conf. Innov. Pract. Technol. Manage. (ICIPTM), Noida, India, 2024, pp. 1–5, doi: 10.1109/ICIPTM59628.2024.10563448.
I. Rozlomii, A. Yarmilko, and S. Naumenko, “Data security of IoT devices with limited resources: Challenges and potential solutions,” in Proc. doors 2024: 4th Edge Computing Workshop, Zhytomyr, Ukraine, CEUR Workshop Proceedings, vol. 3666, pp. 85–96, 2024, doi: 10.55056/ceur-ws.org/Vol-3666/paper13.pdf.
Y. V. Voievodin and I. O. Rozlomii, “Advanced software framework for comparing balancing strategies in container orchestration systems,” in Proc. doors 2024: 4th Edge Computing Workshop, Zhytomyr, Ukraine, CEUR Workshop Proceedings, vol. 3666, pp. 60–69, 2024, doi: 10.55056/ceur-ws.org/Vol-3666/paper09.pdf.
Y. Voievodin and I. Rozlomii, “Application Security Optimization in Container Orchestration Systems Through Strategic Scheduler Decisions,” in Proc. CPITS-2024: Cybersecurity Providing in Information and Telecommunication Systems, Kyiv, Ukraine, CEUR Workshop Proceedings, vol. 3654, pp. 471–478, 2024, doi: 10.5281/zenodo.21132895.
Published
Issue
Section
License
Copyright (c) 2026 Security of Infocommunication Systems and Internet of Things

This work is licensed under a Creative Commons Attribution 4.0 International License.









