Design and Implementation of a Campus-Wide AI-Based Cybersecurity System in Federal University, Kashere, Gombe State
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Background of the Study
Cybersecurity is a critical concern in educational institutions as they face increased threats due to the growing reliance on digital technologies for academic, administrative, and research activities. Federal University, Kashere, Gombe State, like many other universities, is heavily dependent on online services, ranging from online exams and research databases to student portals and communication platforms. However, these systems are often targeted by cybercriminals aiming to disrupt operations, steal sensitive data, or compromise network security (Zahra et al., 2023).
Traditional security measures, such as firewalls and antivirus software, are no longer sufficient in countering the evolving threat landscape. Therefore, there is a growing interest in using Artificial Intelligence (AI) to enhance cybersecurity defenses. AI-based systems are capable of learning from network data and adapting to new threats, offering more efficient and proactive protection against cyberattacks (Ogunleye et al., 2024).
This study aims to design and implement a campus-wide AI-based cybersecurity system at Federal University, Kashere, to enhance its ability to detect, prevent, and respond to security threats in real time. The AI system will leverage machine learning algorithms to identify anomalous behavior, predict potential attacks, and automate defensive measures, thereby improving the overall security posture of the university’s network.
Statement of the Problem
Despite the university's efforts to implement traditional cybersecurity measures, Federal University, Kashere, continues to face security challenges such as unauthorized access, data breaches, and malware infections. The absence of an integrated, intelligent, and adaptive cybersecurity system leaves the university vulnerable to sophisticated cyber threats. This study seeks to address these vulnerabilities by developing an AI-based cybersecurity solution tailored to the university’s needs.
Objectives of the Study
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To design an AI-based cybersecurity system for Federal University, Kashere, focusing on real-time threat detection and response.
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To implement the proposed AI-based cybersecurity system across the campus network.
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To evaluate the effectiveness of the AI-based cybersecurity system in mitigating cyber threats at the university.
Research Questions
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How can an AI-based cybersecurity system be designed and integrated into the existing campus network infrastructure at Federal University, Kashere?
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What are the key advantages of using AI-based systems for cybersecurity compared to traditional methods at the university?
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How effective is the AI-based cybersecurity system in detecting and mitigating cyber threats in real time?
Significance of the Study
The study will significantly enhance the cybersecurity capabilities of Federal University, Kashere, by introducing a state-of-the-art AI-based system. It will serve as a model for other universities seeking to improve their digital security infrastructure and safeguard sensitive academic and administrative data.
Scope and Limitations of the Study
The study is limited to the design, implementation, and evaluation of the AI-based cybersecurity system at Federal University, Kashere. It will not extend to other universities or focus on broader cybersecurity technologies.
Definitions of Terms
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Artificial Intelligence (AI): The simulation of human intelligence processes by machines, particularly in problem-solving and decision-making.
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Cybersecurity System: A collection of tools, policies, and measures aimed at protecting computer networks and systems from cyberattacks and unauthorized access.
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Machine Learning: A subset of AI where systems learn and improve from experience without being explicitly programmed.
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