[HTML][HTML] Machine learning and deep learning techniques for internet of things network anomaly detection—current research trends

SH Rafique, A Abdallah, NS Musa, T Murugan - Sensors, 2024 - mdpi.com
With its exponential growth, the Internet of Things (IoT) has produced unprecedented levels
of connectivity and data. Anomaly detection is a security feature that identifies instances in …

An exploration of challenges associated with machine learning for time series forecasting of COVID-19 community spread using wastewater-based epidemiological …

L Vaughan, M Zhang, H Gu, JB Rose… - Science of The Total …, 2023 - Elsevier
Wastewater-based epidemiology (WBE) has gained increasing attention as a
complementary tool to conventional surveillance methods with potential for significant …

Botnet detection in IoT devices using random forest classifier with independent component analysis

NS Akash, S Rouf, S Jahan… - … of Information and …, 2022 - e-journal.uum.edu.my
With rapid technological progress in the Internet of Things (IoT), it has become imperative to
concentrate on its security aspect. This paper represents a model that accounts for the …

HS-TCN: A semi-supervised hierarchical stacking temporal convolutional network for anomaly detection in IoT

Y Cheng, Y Xu, H Zhong, Y Liu - 2019 IEEE 38th International …, 2019 - ieeexplore.ieee.org
The rapid development of Internet of Things (IoT) accumulates lots of communication data.
Not being processed in time, these massive data increase the difficulty of anomaly detection …

An online anomaly detection approach for unmanned aerial vehicles

C Titouna, F Naït-Abdesselam… - … and Mobile Computing …, 2020 - ieeexplore.ieee.org
A non-predicted and transient malfunctioning of one or multiple unmanned aerial vehicles
(UAVs) is something that may happen over a course of their deployment. Therefore, it is very …

Anomaly detection using LSTM-Autoencoder to predict coal pulverizer condition on Coal-fired power plant

H Pariaman, GM Luciana, MK Wisyaldin, M Hisjam - 2021 - catalog.lib.kyushu-u.ac.jp
Coal pulverizing systems reliability can be ensured effectively by using prognostics and
health management approach. A mathematical model of coal pulverizing system used for …

Choosing machine learning algorithms for anomaly detection in smart building iot scenarios

F Almaguer-Angeles, J Murphy… - 2019 IEEE 5th World …, 2019 - ieeexplore.ieee.org
Internet of Things (IoT) systems produce large amounts of raw data in the form of log files.
This raw data must then be processed to extract useful information. Machine Learning (ML) …

An GMM Method in IoT Approach to Improve Energy Efficiency in Smart Building

R Raja, R Saraswathi - 2023 5th International Conference on …, 2023 - ieeexplore.ieee.org
The rapid growth of commercial building energy use has created a need for innovative
methods for reducing and optimizing building energy use. Building Energy Management …

Road Surface Quality Detection Using Light Weight Neural Network for Visually Impaired Pedestrian

A Chaudhary - 2023 - catalog.lib.kyushu-u.ac.jp
Visually impaired pedestrians often face challenges navigating outdoor environments due to
difficulties in identifying road surface quality. To enhance safety, we propose a deep …

Anomaly detection and root cause diagnosis in cellular networks

M Mdini - 2019 - theses.hal.science
With the evolution of automation and artificial intelligence tools, mobile networks
havebecome more and more machine reliant. Today, a large part of their management tasks …