Artificial Intelligence and Cybersecurity Applications in Modern Education

Abstract

Because it makes adaptive learning, predictive analytics, intelligent tutoring systems, and automated assessment possible, artificial intelligence (AI) is revolutionising education.  In addition to these advantages, the education industry has seen an unparalleled surge in cyberthreats, such as ransomware, phishing, and data breaches, which prey on the very systems intended to modernise education (ENISA, 2020; Jisc, 2020).  In order to critically analyse the relationship between the use of AI and cybersecurity issues in contemporary education, this research synthesises data from 2016–2022.  A taxonomy is put forth that correlates comparable risks and mitigation techniques with AI use-cases in analytics, proctoring, and learning management systems (LMS).  The paper emphasises the dual role of AI as both a solution and a source of security risk by using a mixed-methods approach that includes a systematic review of peer-reviewed studies, survey analysis of institutional practices, and experimental evaluation of machine learning-based intrusion detection systems on benchmark datasets (CICIDS2017, UNSW-NB15) (Ring et al., 2019; Ferrag et al., 2020).  According to the findings, incident rates can be significantly decreased without compromising learning objectives by combining zero-trust principles, privacy-by-design frameworks, and ensemble anomaly detection models (Kindervag, 2010; Cavoukian, 2011; NIST, 2020).  The results support policy conversations and academic debates about how to ensure AI-enabled education for long-term resilience..