Enhancing Network Security Through AI-Powered Access Control in Federal University, Dutsin-Ma, Katsina State
- Project Research
- 1-5 Chapters
- Abstract : Available
- Table of Content: Available
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- Recommended for :
- NGN 5000
Background of the Study
Network security is a critical concern for universities as cyber threats continue to evolve. Traditional access control mechanisms, such as passwords and manual authentication processes, are often insufficient in preventing unauthorized access and security breaches (Bello & Nwafor, 2024). Artificial Intelligence (AI)-powered access control systems offer an advanced solution by automating user authentication, detecting anomalies, and preventing unauthorized network access.
AI-powered access control utilizes machine learning algorithms to analyze login patterns, identify suspicious behavior, and enforce real-time security measures. Techniques such as biometric authentication, behavioral analytics, and anomaly detection enhance security beyond traditional authentication methods (Chukwu et al., 2023).
This study aims to explore how AI-powered access control can strengthen network security in Federal University, Dutsin-Ma, by reducing unauthorized access, improving authentication processes, and enhancing overall network protection.
Statement of the Problem
Federal University, Dutsin-Ma, faces increasing network security threats due to weak authentication mechanisms, password vulnerabilities, and unauthorized access attempts. Traditional access control methods fail to adapt to emerging cyber threats, leaving the institution exposed to potential data breaches and security compromises.
This study investigates the effectiveness of AI-powered access control in enhancing network security and reducing cyber threats in the university.
Objectives of the Study
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To assess the current network security challenges in Federal University, Dutsin-Ma.
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To evaluate the effectiveness of AI-powered access control in mitigating security threats.
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To propose strategies for implementing AI-based security measures in the university.
Research Questions
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What are the major network security challenges faced by Federal University, Dutsin-Ma?
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How effective is AI-powered access control in preventing unauthorized network access?
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What implementation strategies can enhance AI-based access control adoption in the university?
Significance of the Study
This study will contribute to the enhancement of network security by demonstrating the role of AI-powered access control in preventing unauthorized access. The findings will be useful for IT administrators and cybersecurity professionals in Nigerian universities.
Scope and Limitations of the Study
The study focuses on AI-powered access control for network security in Federal University, Dutsin-Ma, Katsina State. It does not examine other AI applications in cybersecurity, such as malware detection or endpoint security.
Definitions of Terms
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AI-Powered Access Control: Security mechanisms that use artificial intelligence to regulate and authenticate network access.
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Biometric Authentication: Security system that verifies users based on biological characteristics such as fingerprints or facial recognition.
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Anomaly Detection: AI technique used to identify unusual patterns that may indicate security threats.
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