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An Efficient IDS Using FIS to Detect DDoS in IoT Networks

Hoang, Trong-Minh and Tran, Nhat-Hoang and Thai, Vu-Long and Nguyen, Dinh-Long and Nguyen, Nam-Hoang (2022) An Efficient IDS Using FIS to Detect DDoS in IoT Networks. In: NAFOSTED Conference on Information and Computer Science (NICS).

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The growing Internet of Things (IoT) applications of today have brought numerous benefits to our lives. In addition, cyber-attacks are growing as a result of increasingly sophisticated and violent attacks. Detection systems that serve as security protection against emerging attacks are also being developed using machine learning techniques. However, many additional challenges continue to emerge as demand for Intrusion Detection System (IDS) deployment at the edge network, where resource-constrained devices exist, continues to increase. These devices require a database with a high level of accuracy for attack detection. This research provides a Fuzzy-based IDS for detecting DDOS attacks with over 99 percent accuracy rate that is deployable on edge computing using the IoT23 dataset.

Item Type: Conference or Workshop Item (Paper)
Subjects: Electronics and Communications > Communications
Divisions: Advanced Insitute of Engineering and Technology (AVITECH)
Faculty of Electronics and Telecommunications (FET)
Depositing User: Nguy�n Nam Hoàng
Date Deposited: 10 Feb 2023 07:29
Last Modified: 10 Feb 2023 07:29

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