eprintid: 4787
rev_number: 8
eprint_status: archive
userid: 353
dir: disk0/00/00/47/87
datestamp: 2023-02-10 07:29:23
lastmod: 2023-02-10 07:29:23
status_changed: 2023-02-10 07:29:23
type: conference_item
metadata_visibility: show
creators_name: Hoang, Trong-Minh
creators_name: Tran, Nhat-Hoang
creators_name: Thai, Vu-Long
creators_name: Nguyen, Dinh-Long
creators_name: Nguyen, Nam-Hoang
creators_id: hoangtrongminh@ptit.edu.vn
creators_id: hoangtn.B18VT178@stu.ptit.edu.vn
creators_id: longtv.B18VT268@stu.ptit.edu.vn
creators_id: longnd@ptit.edu.vn
creators_id: hoangnn@vnu.edu.vn
title: An Efficient IDS Using FIS to Detect DDoS in IoT Networks
ispublished: pub
subjects: Communications
divisions: avitech
divisions: fac_fet
abstract: 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.
date: 2022-10
date_type: published
full_text_status: none
pres_type: paper
pagerange: 1-6
event_title: NAFOSTED Conference on Information and Computer Science (NICS)
event_type: conference
refereed: TRUE
citation:   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).