Jul 2026· International Journal of Electrical Engineering and Computer Science· 0 citations· 13 references
TL;DR
Some operational and technical challenges that affect the adoption of effective cybersecurity prac-tices within e-government infrastructures are identified and the importance of scalable, cost-effective, and integrated monitoring infrastructures to manage cybersecurity proactively in developing countries are highlighted.
Abstract
E-government digital platforms are often attacked by sophisticated cybersecurity threats because of the sensitive nature of the information and services they provide. The analysis finds that these systems have vulnerabilities due to fragmented security architectures, not enough skilled personnel, limited budgets, and reactive security approaches, particularly within developing countries such as Zambia. This study reviews existing research on cybersecurity challenges affecting e-government systems, focusing on Gov-ernment-to-Business (G2B) digital platforms in developing countries. It also examines established cyber-security frameworks, including Defence-in-Depth (DiD), NIST CSF, ISO/IEC 27001, and the Zero Trust model. The study also reviews the role of Centralized Security Monitoring Platforms (CSMPs) integrated with Intrusion Detection and Prevention Platforms (IDPPs) in improving threat visibility, event correla-tion, and coordinated incident response. A lightweight validation approach is carried out using a virtual-ized environment, which relies on open-source platforms such as pfSense, Suricata, and Wazuh to show how the centralization of monitoring increases situational awareness and correlates events to show the relevance of the proposed solution within a resource-constrained environment. The study further identi-fied some operational and technical challenges that affect the adoption of effective cybersecurity prac-tices within e-government infrastructures and highlights the importance of scalable, cost-effective, and integrated monitoring infrastructures to manage cybersecurity proactively in developing countries.
A multi-level cybersecurity and privacy framework that integrates complementary controls across physical, network, endpoint, application, data, identity and access management, monitoring and incident response, and human and policy domains is developed.
A better AI-driven SIEM framework that combines machine learning-based threat detection with an automated incident response layer that follows security playbooks that have already been set up is suggested.
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The results indicate that a NIST-based approach can assist organizations in identifying and prioritizing cybersecurity risks, strengthening data protection mechanisms, enhancing incident readiness, and optimizing continuous security monitoring.
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