Enhancing the Security of School Databases Using AI-Based Intrusion Detection Systems in Secondary Schools in Minna, Niger State
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Background of the Study
With the increasing digitization of school operations, databases play a crucial role in storing and managing student records, academic results, administrative documents, and financial transactions. However, as secondary schools in Minna, Niger State, continue to adopt digital platforms for data management, they become vulnerable to cyber threats such as unauthorized access, data breaches, malware attacks, and insider threats (Adebayo & Yusuf, 2024). Traditional security mechanisms such as password authentication and firewalls are no longer sufficient to safeguard school databases against sophisticated cyberattacks (Okonkwo & Salisu, 2023).
Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) offer an innovative approach to enhancing database security in educational institutions. AI-powered IDS use machine learning algorithms to monitor network traffic, detect anomalies, and identify potential security breaches in real time (Olawale & Musa, 2024). Unlike conventional security measures, AI-based IDS can adapt to evolving cyber threats, detect unusual patterns, and automatically respond to potential intrusions before they cause significant damage (Adebayo & Ibrahim, 2023). This proactive approach is essential for protecting sensitive school data from cybercriminals and ensuring data integrity.
Despite the advantages of AI-driven security solutions, many secondary schools in Minna still rely on outdated security measures that leave their databases vulnerable to attacks. The lack of awareness, technical expertise, and financial resources limits the adoption of AI-based IDS in school database security management (Okonkwo & Salisu, 2024). Cases of data breaches, unauthorized data modifications, and identity theft among students and staff have been reported, emphasizing the need for a more robust security framework.
This study aims to explore the effectiveness of AI-based IDS in enhancing school database security, identify current security challenges, and propose a framework for the adoption of AI-driven intrusion detection solutions in secondary schools in Minna, Niger State.
Statement of the Problem
Secondary schools in Minna face increasing cybersecurity threats due to their growing reliance on digital databases. These databases store critical information, including student records, staff details, and financial transactions, making them attractive targets for cybercriminals (Olawale & Musa, 2023). The existing security measures, such as password authentication and manual monitoring, are insufficient to prevent sophisticated cyberattacks, resulting in data breaches, unauthorized modifications, and information theft (Adebayo & Yusuf, 2024).
AI-based IDS offer real-time anomaly detection and automated response mechanisms, yet their implementation in secondary schools remains limited. Many school administrators lack awareness of advanced security solutions, and budget constraints hinder the deployment of AI-driven security frameworks (Okonkwo & Salisu, 2024). Additionally, there is a gap in research regarding the effectiveness of AI-based IDS in securing school databases, making it difficult for educational institutions to adopt data-driven security strategies.
This study seeks to address these challenges by assessing the impact of AI-based IDS on school database security, examining barriers to adoption, and proposing implementation strategies for secondary schools in Minna, Niger State.
Objectives of the Study
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To assess the current security challenges affecting school database management in secondary schools in Minna.
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To evaluate the effectiveness of AI-based Intrusion Detection Systems in enhancing school database security.
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To propose an AI-driven database security framework for secondary schools in Minna.
Research Questions
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What are the major cybersecurity challenges affecting school database management in secondary schools in Minna?
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How does AI-based Intrusion Detection enhance the security and protection of school databases?
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What strategies can be implemented to facilitate the adoption of AI-based IDS in school database security?
Research Hypotheses
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Traditional security measures in secondary schools in Minna are inadequate for preventing database intrusions.
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AI-based Intrusion Detection Systems significantly improve the security and protection of school databases.
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Schools that implement AI-based IDS experience fewer cybersecurity breaches and enhanced data integrity.
Significance of the Study
This study is significant as it highlights the role of AI-driven IDS in strengthening school database security. By examining the limitations of traditional security mechanisms and evaluating the benefits of AI-based IDS, the research provides valuable insights for school administrators, policymakers, and cybersecurity professionals. The findings will support the development of advanced security strategies that protect sensitive student and administrative data. Additionally, this study will contribute to existing literature on AI applications in cybersecurity, serving as a reference for future research on data security in educational institutions.
Scope and Limitations of the Study
This study is limited to secondary schools in Minna Local Government Area, Niger State. It focuses on identifying security challenges, evaluating AI-based IDS effectiveness, and proposing implementation strategies. The study does not cover other local government areas, primary schools, or higher institutions.
Definitions of Terms
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Intrusion Detection System (IDS): A security mechanism that monitors network traffic and detects unauthorized access or potential cyber threats.
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Artificial Intelligence (AI): The simulation of human intelligence in machines, enabling them to learn, analyze data, and make automated decisions.
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Cybersecurity: The practice of protecting computer systems, networks, and digital data from unauthorized access, cyberattacks, and data breaches.
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