Background of the Study
As universities increasingly migrate their data and services to the cloud, the need for robust cybersecurity measures to protect cloud-based assets becomes more critical. Federal University Lafia in Nasarawa State is among the universities leveraging cloud technologies to improve access to resources and enhance collaboration. While cloud computing offers numerous benefits such as scalability, flexibility, and cost savings, it also introduces new security challenges, particularly in threat detection and management. Without appropriate security protocols and monitoring systems, universities may become targets of cyberattacks that compromise sensitive data.
Cloud-based cybersecurity threat management systems offer a promising solution by providing real-time monitoring, automated threat detection, and rapid response capabilities. These systems can aggregate and analyze vast amounts of data from various cloud services, identify potential security threats, and trigger appropriate security responses. However, the effectiveness of cloud-based cybersecurity threat management systems in protecting university cloud infrastructures remains underexplored in Nigeria. This study aims to evaluate the use of such systems at Federal University Lafia and assess their ability to detect and mitigate cyber threats.
Statement of the Problem
Federal University Lafia has adopted cloud-based services for various academic and administrative functions, but the university faces growing concerns about the security of its cloud infrastructure. The lack of comprehensive cybersecurity threat management systems to monitor and respond to potential attacks exposes the university’s cloud services to significant risks. As such, there is a need to evaluate the effectiveness of cloud-based cybersecurity threat management systems in ensuring the security of the university’s cloud-based assets.
Objectives of the Study
To evaluate the effectiveness of cloud-based cybersecurity threat management systems at Federal University Lafia.
To assess the performance of cloud-based threat detection and response mechanisms in the university's cloud infrastructure.
To propose recommendations for improving the security of cloud-based services at Federal University Lafia.
Research Questions
How effective are cloud-based cybersecurity threat management systems in protecting the cloud infrastructure at Federal University Lafia?
What are the strengths and limitations of using cloud-based systems for cybersecurity threat management in a university setting?
How do cloud-based threat management systems compare to traditional on-premises security solutions in detecting and mitigating cyber threats?
Significance of the Study
This study will provide valuable insights into the effectiveness of cloud-based cybersecurity threat management systems in Nigerian universities. By evaluating the security posture of Federal University Lafia’s cloud infrastructure, the research will contribute to improving the overall cybersecurity framework at the institution and potentially offer a model for other universities in Nigeria seeking to enhance their cloud security.
Scope and Limitations of the Study
The study will focus on the evaluation of cloud-based cybersecurity threat management systems at Federal University Lafia. The research will specifically examine how well these systems perform in terms of detecting and mitigating cyber threats. Limitations include the potential difficulty in accessing data on actual threat incidents and the reliance on the university's existing cloud infrastructure for evaluation.
Definitions of Terms
Cloud Computing: The delivery of computing services such as storage, processing, and networking over the internet, typically on a pay-per-use basis.
Cybersecurity Threat Management: The process of identifying, assessing, and mitigating cybersecurity risks to protect systems and data.
Cloud Security: The set of policies, technologies, and controls designed to protect cloud-based systems, data, and infrastructure.
Threat Detection: The process of identifying potential cybersecurity threats in real-time through analysis of network or system activities.
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