Secured Online Learning in COVID-19 Pandemic using Deep Learning Methods

Abstract

With the outbreak of the global pandemic covid-19, most educational institutions across India have moved towards the usage of online teaching platforms Viz., Google Meet, Zoom, Webex, and Microsoft teams to process learning continuity. In research and development, it is observed that meager importance is given to address the issues of securing e- learning systems. Securing an e-learning system is a unique challenge faced in India as many systems are accessed and managed through the internet by numerous users distributed over diverse networks. Moreover, the online teaching platforms are open, distributed, and interactive; hence, it becomes challenging to ensure that every user has access to the correct information. Building trust will leverage the usage of online teaching systems in terms of security, usability, and protection of personal information. The key focus of this paper is to analyze the existing online and remote learning tools and identify the level of cyberattacks. This article also explores recent progress in novel ICT engineering paradigms in cyber assurance and protection. The paper proposes a cyber-security framework using cutting-edge technologies like AI and Deep Learning to fight against cyber-attacks.