Deep learning-enabled anomaly detection for IoT systems
Abstract Internet of Things (IoT) systems have become an intrinsic technology in various
industries and government services. Unfortunately, IoT devices and networks are known to …
industries and government services. Unfortunately, IoT devices and networks are known to …
[HTML][HTML] Enhancing IoT network security through deep learning-powered Intrusion Detection System
The rapid growth of the Internet of Things (IoT) has brought about a global concern for the
security of interconnected devices and networks. This necessitates the use of efficient …
security of interconnected devices and networks. This necessitates the use of efficient …
[HTML][HTML] A systematic literature review of recent lightweight detection approaches leveraging machine and deep learning mechanisms in Internet of Things networks
GAL Mukhaini, M Anbar, S Manickam… - Journal of King Saud …, 2023 - Elsevier
Abstract The Internet of Things (IoT) connects daily use devices to the Internet, such as
home appliances, health care equipment, sensors, and industrial devices. Concurrently …
home appliances, health care equipment, sensors, and industrial devices. Concurrently …
Fog-cloud based intrusion detection system using Recurrent Neural Networks and feature selection for IoT networks
Deep learning (DL) techniques are being widely researched for their effectiveness in
detecting cyber intrusions against the Internet of Things (IoT). Time sensitive Critical …
detecting cyber intrusions against the Internet of Things (IoT). Time sensitive Critical …
[HTML][HTML] Investigation on identify the multiple issues in IoT devices using Convolutional Neural Network
Abstract The Internet of Things (IoT) is an innovative technology that makes it possible for
physical objects like sensors, cameras, household appliances, and other objects to interact …
physical objects like sensors, cameras, household appliances, and other objects to interact …
TS-IDS: Traffic-aware self-supervised learning for IoT Network Intrusion Detection
With recent advances in the Internet of Things (IoT) technology, more people can have
instant and easy access to the IoT network of vast and diverse interconnected devices (eg …
instant and easy access to the IoT network of vast and diverse interconnected devices (eg …
Anomaly detection in Internet of medical Things with Blockchain from the perspective of deep neural network
J Wang, H Jin, J Chen, J Tan, K Zhong - Information Sciences, 2022 - Elsevier
IoMT technology has many advantages in healthcare system, such as optimizing the
medical service model, improving the efficiency of hospital operation and management, and …
medical service model, improving the efficiency of hospital operation and management, and …
An explainable and resilient intrusion detection system for industry 5.0
D Javeed, T Gao, P Kumar… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Industry 5.0 is a emerging transformative model that aims to develop a hyperconnected,
automated, and data-driven industrial ecosystem. This digital transformation will boost …
automated, and data-driven industrial ecosystem. This digital transformation will boost …
Network intrusion detection based on n-gram frequency and time-aware transformer
Network intrusion detection system plays a critical role in protecting the target network from
attacks. However, most existing detection methods cannot fully utilize the information …
attacks. However, most existing detection methods cannot fully utilize the information …
Crsf: An intrusion detection framework for industrial internet of things based on pretrained cnn2d-rnn and svm
S Li, G Chai, Y Wang, G Zhou, Z Li, D Yu, R Gao - IEEE Access, 2023 - ieeexplore.ieee.org
The traditional support vector machine (SVM) requires manual feature extraction to improve
classification performance and relies on the expressive power of manually extracted …
classification performance and relies on the expressive power of manually extracted …