Social Engineering Attacks in E-Government System Detection and Prevention

Abstract

Purpose: E-Government system emerged as a novel public service provision platform that enables governance in an efficient and transparent manner globally. However, despite the success recorded so far by the increase in the use of information and communication technology (ICT) and E-government for public service provision. Social engineering attack (SEA) is one of the challenging information security attacks that prove to be difficult to tackle. This is because the attackers leverage on peoples’ weakness to exploit the system instead of technical vulnerabilities.Design/Methodology/Approach: This paper uses PESTLE (political, economic, social, technology, legal and environment) analysis to critically evaluate the external factors affecting SEAs in E-government system. Findings/Result: The study identified phishing, Baiting, Pretexting, Quid Pro Quo, Honey Trap, Tail Gating, and Pharming as the major SEA techniques used to exploit E-government systems. Furthermore, the author suggest training and awareness programme as the most effective way to detect as well as prevent SEA in E-government system. Users should be aware of the languages with terms requesting urgent response as well as unusual or unexpected situation in a suspicious messages or attachment as factors to detect SEA. Technical controls using natural language processes (NLP), securitypolicies, multifactor authentication (MFA) as well as secured preservation of confidential information from suspicious users are some of the SEA preventive measures.Originality/Value: Aflexible and efficient interaction among citizens, businesses and government organizations is a critical factor for successful E-Government system. SEA is one of major challenges affecting communications in E-government system that requires attention. In conclusion, studies toward technological approach for solution of SEAin E-government is recommended.Paper Type: Conceptual Research.

Authors and Affiliations

Musa Midila Ahmed

Keywords

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  • EP ID EP714599
  • DOI https://doi.org/10.5281/zenodo.6085386
  • Views 80
  • Downloads 0

How To Cite

Musa Midila Ahmed (2022). Social Engineering Attacks in E-Government System Detection and Prevention. INTERNATIONAL JOURNAL OF APPLIED ENGINEERING AND MANAGEMENT LETTERS (IJAEML), 6(1), -. https://europub.co.uk/articles/-A-714599