Enhancement of the Electronic Governance Security Infrastructure Utilizing Deep Learning Techniques

Abstract

Recent years have seen a growth in the field of artificial intelligence (AI), with deep learning (DL) approaches offering up new opportunities for cutting-edge outcomes in an increasing number of fields. The use of technology in e-government applications to improve both the systems and citizen-government interactions is still hindered by a variety of challenges. The authors explore the issues with e-government systems in this chapter and offer a paradigm for automating and streamlining e-government services. Convolutional neural networks (CNNs) and other state-of-the-art techniques, such as transfer learning and deep ensemble learning, have been used to classify problems with high accuracy. Our overall objective is to use trustworthy AI methods to improve the current state of e-government services and lower processing times, costs, and citizen enjoyment. Several instances will also be included in the chapter to demonstrate how DL techniques can be applied in practical situations.