Cruciality of securing user data due to increasing Digital Learner traffic over the Internet using Adversarial Neural Cryptography

Abstract

In recent years, the whole globe has been afflicted with a devastating viral virus known as COVID-19 that has interrupted the operations of every organization. COVID-19 has significantly impacted education, causing it to struggle to function as smoothly as before. However, it has also ushered in a new era of e-learning, necessitating the provision of suitable facilities for users and learners. The growing number of users has led to an increase in digital threats to vulnerable systems on the widespread web of devices. The need for more diverse, versatile, and robust techniques is rising day by day, and Adversarial Neural Cryptography has the potential to be in the Line. The notions of Machine Learning and Digital Securities are being implemented in numerous manners for which ANC can perform the role of new technology to secure communication lines of a Digital learner from several learning platforms over the Cloud. This paper explores the possible threats, reasons, and potential steps taken to secure the user of the Digital Learning Platforms by various organizations. In extension to this, the concept of Adversarial Neural Cryptography is also introduced in the light of E-Learning Platforms with a conceptual model to secure communication.