GBDT-IL: Incremental Learning of Gradient Boosting Decision Trees to Detect Botnets in Internet of Things
The rapid development of the Internet of Things (IoT) has brought many conveniences to our daily life. However, it has also introduced various security risks that need to be addressed. The proliferation of IoT botnets is one of these risks. Most of researchers have had some success in IoT botnet det...
Main Authors: | Ruidong Chen, Tianci Dai, Yanfeng Zhang, Yukun Zhu, Xin Liu, Erfan Zhao |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2024-03-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/24/7/2083 |
Similar Items
-
Examination of Traditional Botnet Detection on IoT-Based Bots
by: Ashley Woodiss-Field, et al.
Published: (2024-02-01) -
A Survey on Botnets, Issues, Threats, Methods, Detection and Prevention
by: Harry Owen, et al.
Published: (2022-02-01) -
IoT Botnet Detection Using Autoencoders and Decision Trees
by: Susanto Susanto, et al.
Published: (2023-11-01) -
Lightweight Internet of Things Botnet Detection Using One-Class Classification
by: Kainat Malik, et al.
Published: (2022-05-01) -
Botnet detection in the internet-of-things networks using convolutional neural network with pelican optimization algorithm
by: Swapna Thota, et al.
Published: (2024-01-01)