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Moosa, Muhammad Aashiq (2023) Detecting and Analysis of DDoS Attack using a Collaborative Network Monitoring Stack. Masters thesis, Dublin, National College of Ireland.
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Abstract
In recent years, distributed denial of service (DDoS) assaults have become more common and have developed as a common means of targeting entities. These assaults can be used to make money or to harm an organization’s network and systems. Much of the recent research in this area has been on using various machine learning approaches to recognize and thwart these attacks. Even while these techniques frequently have excellent accuracy rates, they sometimes struggle to detect zero-day vulnerabilities or handle heavy network traffic. This research moves its emphasis from DDoS detection to the development of a cost-effective network monitoring stack. The intended solution will deliver real-time insights into a simulated network environment while also incorporating a machine learning engine for improved DDoS detection. This initiative aims to provide organizations with a comprehensive, cost-effective solution that goes beyond DDoS mitigation by emphasizing a more economical and effective monitoring system.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Vangujar, Apurva UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
| Divisions: | School of Computing > Master of Science in Cyber Security |
| Depositing User: | Tamara Malone |
| Date Deposited: | 24 Oct 2024 14:44 |
| Last Modified: | 24 Oct 2024 14:44 |
| URI: | https://norma.ncirl.ie/id/eprint/7134 |
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