将基于人工智能的网络安全措施与传统网络安全措施整合到在线高等教育环境中:挑战、机遇和前景

Medha Mohan Ambali Parambil , Jaloliddin Rustamov , Soha Galalaldin Ahmed , Zahiriddin Rustamov , Ali Ismail Awad, Nazar Zaki, Fady Alnajjar
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引用次数: 0

摘要

在线学习在高等教育中的迅速普及带来了巨大的网络安全挑战。随着教育机构越来越依赖数字平台,它们正面临着可能危及敏感数据和破坏运营的网络威胁。本系统性文献综述探讨了如何将人工智能(AI)融入传统方法,以应对在线高等教育中的网络安全风险。综述结合了相关文献的定性综述和使用 PRISMA 准则进行的定量荟萃分析,确保对整合过程有全面的了解。对最普遍的网络安全威胁进行了研究,并比较了基于人工智能的方法和传统方法在缓解这些挑战方面的有效性。此外,还分析了网络安全解决方案中最有效的人工智能技术,并比较了它们在不同情况下的表现。此外,研究还考虑了与将人工智能融入传统网络安全方法相关的关键伦理和技术因素。研究结果表明,虽然基于人工智能的技术为威胁检测、身份验证和隐私保护提供了前景广阔的解决方案,但其成功实施需要仔细考虑数据隐私、公平性、透明度和稳健性。跨学科合作、自动系统和人类对人工智能模型的持续监控以及制定全面指导方针以确保在网络安全领域负责任地、合乎道德地使用人工智能的必要性都得到了强调。本综述的研究结果为教育机构、教育工作者和学生提供了可操作的见解,有助于促进安全、有弹性的在线学习环境的发展。所确定的伦理和技术考虑因素可作为将人工智能负责任地融入在线高等教育领域网络安全的基础。
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Integrating AI-based and conventional cybersecurity measures into online higher education settings: Challenges, opportunities, and prospects
The rapid adoption of online learning in higher education has resulted in significant cybersecurity challenges. As educational institutions increasingly rely on digital platforms, they are facing cyber threats that can compromise sensitive data and disrupt operations. This systematic literature review explores the integration of artificial intelligence (AI) into traditional methods to address cybersecurity risks in online higher education. The review integrates a qualitative synthesis of relevant literature and a quantitative meta-analysis using PRISMA guidelines, ensuring comprehensive insights into the integration process. The most prevalent cybersecurity threats are examined, and the effectiveness of AI-based and conventional approaches in mitigating these challenges is compared. Additionally, the most effective AI techniques in cybersecurity solutions are analyzed, and their performance is compared across different contexts. Furthermore, the review considers the key ethical and technical considerations associated with integrating AI into traditional cybersecurity methods. The findings reveal that while AI-based techniques offer promising solutions for threat detection, authentication, and privacy preservation, their successful implementation requires careful consideration of data privacy, fairness, transparency, and robustness. The importance of interdisciplinary collaboration, continuous monitoring of AI models—by automated systems and humans—and the need for comprehensive guidelines to ensure responsible and ethical use of AI in cybersecurity are highlighted. The findings of this review provide actionable insights for educational institutions, educators, and students, helping to facilitate the development of secure and resilient online learning environments. The identified ethical and technical considerations can serve as a foundation for the responsible integration of AI into cybersecurity within the online higher-education sector.
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来源期刊
CiteScore
16.80
自引率
0.00%
发文量
66
审稿时长
50 days
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