The influence of deep learning in detecting cyber attacks on e-government applications

Loveleen Gaur, Raja Majid Ali Ujjan, Manzoor Hussain

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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.
Original languageEnglish
Title of host publicationCybersecurity Measures for E-Government Frameworks
EditorsLoveleen Gaur, Raja Majid Ali Ujjan, Manzoor Hussain
PublisherIGI Publishing
Pages107-122
Number of pages16
ISBN (Print)9781799896241, 1799896242, 9781799896258, 978199896265
DOIs
Publication statusPublished - 11 Mar 2022

Publication series

NameAdvances in Electronic Government, Digital Divide, and Regional Development
PublisherIdea Group Inc
ISSN (Print)2326-9103

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