Background of the Study
In an increasingly interconnected world, universities face growing threats to their networks and data. Federal University Lokoja in Kogi State, like many other academic institutions, relies heavily on network infrastructure to support teaching, research, and administration. The complexity and scale of modern university networks make them attractive targets for cyber-attacks, leading to potential data breaches and loss of academic resources. To mitigate these risks, universities need intelligent, adaptive security systems that can detect and respond to potential threats in real-time.
The advent of Artificial Intelligence (AI) in cybersecurity offers promising solutions for universities to monitor and defend their networks proactively. AI-based tools can analyze vast amounts of network traffic and security data, identify unusual patterns, and predict potential threats before they cause significant harm. In Lokoja, the need for such a tool is crucial to strengthen the network defenses at Federal University Lokoja. However, while many AI-based cybersecurity tools have been developed, their application within the context of university networks in Nigeria remains limited. Therefore, a tailored AI-driven network security analytics tool is needed to address the unique challenges faced by universities in Kogi State.
Statement of the Problem
The increasing dependence on digital platforms at Federal University Lokoja has made its network more vulnerable to cyber threats. Current security systems in place are largely reactive and fail to detect and mitigate potential threats before they cause damage. With the growing volume and sophistication of cyber-attacks targeting academic institutions, there is a need for a more proactive and intelligent approach to network security. AI-based network security analytics tools have been shown to improve detection accuracy and speed, yet such systems have not been adequately developed or deployed in Nigerian universities. Without an AI-based tool, the university risks exposure to potential breaches, loss of academic data, and compromised student and faculty privacy.
Objectives of the Study
To develop an AI-based network security analytics tool tailored to the needs of Federal University Lokoja.
To evaluate the effectiveness of the tool in detecting and mitigating potential network threats in real-time.
To compare the AI-based tool's performance with traditional network security systems used at the university.
Research Questions
How can AI-based network security tools enhance the detection and prevention of cyber-attacks at Federal University Lokoja?
What are the key features and algorithms necessary for an AI-based network security tool in a university setting?
How does the AI-based security tool perform in comparison to conventional security tools in terms of threat detection and response time?
Significance of the Study
This study aims to improve the network security infrastructure of Federal University Lokoja by developing an AI-based tool capable of proactively identifying and mitigating cyber threats. The findings could provide valuable insights for other Nigerian universities seeking to enhance their cybersecurity measures, ultimately contributing to safer online learning and administrative environments.
Scope and Limitations of the Study
The scope of the study is limited to the development and evaluation of an AI-based network security analytics tool for Federal University Lokoja. The research will focus on real-time threat detection and prevention capabilities within the university's existing network infrastructure. The study will be limited to Federal University Lokoja’s network environment and will not be applicable to other institutions in Kogi State or beyond.
Definitions of Terms
Artificial Intelligence (AI): The simulation of human intelligence processes by machines, especially computer systems, to solve complex problems.
Network Security: The practice of protecting the integrity, confidentiality, and accessibility of computer networks and data.
Analytics Tool: A software application designed to process and analyze data to identify patterns, trends, or threats.
Threat Detection: The process of identifying potential security threats in a network environment.
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