The Influence of Deep Learning in Detecting Cyber Attacks on E-Government Applications
Loveleen Gaur, Raja Majid Ali Ujjan, Manzoor Hussain
Abstract
The digitalization revolution plays a crucial role in every government administration. It manages a considerable volume of user information and is currently seeing an increase in internet access. The absence of unorganized information, on the other hand, adds to the difficulty of data analysis. Data mining approaches have recently become more popular for addressing a variety of e-governance concerns, particularly data management, data processing, and so on. This chapter identifies and compares several existing data mining and data warehouses in e-government. Deep learning is a subset of a larger class of machine learning techniques that combine artificial neural networks. The significance and difficulties of e-governance are highlighted for future enhancement. As a result, with the growth of e-governance, risk and cyber-attacks have increased these days. Furthermore, the few e-governance application performance evaluations are included in this chapter. The purpose of this chapter is to focus on deep learning applications of e-governance in detecting cyber-attacks.