[HTML][HTML] IoT anomaly detection methods and applications: A survey
A Chatterjee, BS Ahmed - Internet of Things, 2022 - Elsevier
Ongoing research on anomaly detection for the Internet of Things (IoT) is a rapidly
expanding field. This growth necessitates an examination of application trends and current …
expanding field. This growth necessitates an examination of application trends and current …
Learning-based methods for cyber attacks detection in IoT systems: A survey on methods, analysis, and future prospects
Internet of Things (IoT) is a develo** technology that provides the simplicity and benefits of
exchanging data with other devices using the cloud or wireless networks. However, the …
exchanging data with other devices using the cloud or wireless networks. However, the …
A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT
The increasing trend toward using the Internet of Things (IoT) increased the number of
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …
[HTML][HTML] Federated learning for malware detection in IoT devices
Billions of IoT devices lacking proper security mechanisms have been manufactured and
deployed for the last years, and more will come with the development of Beyond 5G …
deployed for the last years, and more will come with the development of Beyond 5G …
Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review
Internet of Things (IoT) technology is prospering and entering every part of our lives, be it
education, home, vehicles, or healthcare. With the increase in the number of connected …
education, home, vehicles, or healthcare. With the increase in the number of connected …
A feature selection algorithm for intrusion detection system based on pigeon inspired optimizer
Feature selection plays a vital role in building machine learning models. Irrelevant features
in data affect the accuracy of the model and increase the training time needed to build the …
in data affect the accuracy of the model and increase the training time needed to build the …
GGWO: Gaze cues learning-based grey wolf optimizer and its applications for solving engineering problems
In this article, an improved variant of the grey wolf optimizer (GWO) named gaze cues
learning-based grey wolf optimizer (GGWO) is proposed. The main intentions are to reduce …
learning-based grey wolf optimizer (GGWO) is proposed. The main intentions are to reduce …
An optimized CNN-based intrusion detection system for reducing risks in smart farming
Smart farming is a well-known and superior method of managing a farm, becoming more
prevalent in today's contemporary agricultural practices. Crops are monitored for their …
prevalent in today's contemporary agricultural practices. Crops are monitored for their …
Botnet Attack Detection by Using CNN‐LSTM Model for Internet of Things Applications
The Internet of Things (IoT) has grown rapidly, and nowadays, it is exploited by cyber attacks
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
on IoT devices. An accurate system to identify malicious attacks on the IoT environment has …
Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm
Monthly streamflow forecasting is required for short-and long-term water resources
management especially in extreme events such as flood and drought. Therefore, there is …
management especially in extreme events such as flood and drought. Therefore, there is …