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Irobunda, Uche Lawrence (2023) Securing and Detecting Attacks in Industrial IoT: An Efficient Intrusion Detection System (IDS) to detect the DOS Attack in IIoT. Masters thesis, Dublin, National College of Ireland.
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Abstract
A large rise in the number of Internet of Things (IoT) devices has been caused by the quick development of interconnected computer devices and the appearance of new network technologies. Remote monitoring and cognitive analytics are being introduced with the Industrial Internet of Things (IIoT), resulting in further developments. While these gadgets simplify and automate routine tasks, they also present serious security dangers.
Implementing an intrusion detection system (IDS) and assessing its effectiveness within an Internet of Things (IoT) network are the main goals of this thesis. The goal of the study is to ascertain how well the IDS works to improve the IoT network's security and performance. The study specifically focuses on detecting and mitigating DOS attacks using SVM classification to detect cyber-attack on the network.
The study highlights the significance of integrating an IDS equipped with the ability to detect unusual traffic using SVM classification and a dataset.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Verma, Rohit 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 T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > Computer networks > Internet of things |
| Divisions: | School of Computing > Master of Science in Cyber Security |
| Depositing User: | Tamara Malone |
| Date Deposited: | 15 Jan 2024 16:37 |
| Last Modified: | 15 Jan 2024 16:37 |
| URI: | https://norma.ncirl.ie/id/eprint/6913 |
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