Development of a Distributed Denial-of-Service (DDoS) Mitigation System in Federal University, Gashua, Yobe State
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- 1-5 Chapters
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- Table of Content: Available
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- NGN 5000
Background of the Study
Distributed Denial-of-Service (DDoS) attacks have become one of the most significant threats to network security in academic institutions. These attacks overwhelm network resources by generating excessive traffic, causing disruptions to online services. Universities, such as Federal University, Gashua, rely on digital platforms for administrative tasks, research collaboration, and academic activities, making them attractive targets for cybercriminals.
DDoS attacks can cripple institutional networks, affecting online learning portals, email services, and student management systems. Traditional security measures, such as firewalls and intrusion detection systems, often fail to handle large-scale DDoS attacks effectively. Developing an advanced mitigation system that incorporates real-time traffic analysis, anomaly detection, and automated response mechanisms is essential for ensuring network resilience.
This study aims to develop a DDoS mitigation system for Federal University, Gashua, leveraging modern security strategies such as AI-driven threat detection and cloud-based scrubbing services. The proposed system will enhance network stability and security, preventing service disruptions caused by malicious traffic.
Statement of the Problem
The growing frequency and sophistication of DDoS attacks pose a severe challenge to the security and availability of academic networks. Federal University, Gashua, has experienced periodic network slowdowns and service disruptions, which may be linked to potential DDoS attacks. Existing security mechanisms lack the capability to detect and mitigate large-scale traffic floods effectively.
Without a robust DDoS mitigation system, the university risks prolonged downtime, financial losses, and compromised academic activities. Many traditional defense mechanisms rely on static rules and manual intervention, which are ineffective against evolving attack patterns. A proactive and automated mitigation system is required to enhance network security and ensure uninterrupted services.
Objectives of the Study
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To develop a DDoS mitigation system for Federal University, Gashua.
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To analyze the impact of DDoS attacks on the university’s network performance.
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To evaluate modern DDoS mitigation strategies for improving network resilience.
Research Questions
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How do DDoS attacks impact the network performance of Federal University, Gashua?
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What are the limitations of existing DDoS mitigation techniques?
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How can an automated DDoS mitigation system improve network security?
Scope and Limitations of the Study
This study focuses on developing a DDoS mitigation system for Federal University, Gashua, Yobe State. It will analyze the impact of DDoS attacks and propose mitigation strategies. Limitations include data availability and implementation costs.
Definitions of Terms
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DDoS Attack: A cyberattack that floods a network with excessive traffic to disrupt services.
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Anomaly Detection: Identifying unusual patterns in network traffic.
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Scrubbing Service: A cloud-based solution that filters malicious traffic before it reaches the target network.
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