[HTML][HTML] Deep residual learning for image recognition: A survey
Deep Residual Networks have recently been shown to significantly improve the
performance of neural networks trained on ImageNet, with results beating all previous …
performance of neural networks trained on ImageNet, with results beating all previous …
[HTML][HTML] Learning-based methods for cyber attacks detection in IoT systems: A survey on methods, analysis, and future prospects
Internet of Things (IoT) is a developing 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 …
[HTML][HTML] A hybrid intrusion detection model using ega-pso and improved random forest method
AK Balyan, S Ahuja, UK Lilhore, SK Sharma… - Sensors, 2022 - mdpi.com
Due to the rapid growth in IT technology, digital data have increased availability, creating
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
novel security threats that need immediate attention. An intrusion detection system (IDS) is …
PPSF: A privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities
With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of
urbanization. IoT networks allow distributed smart devices to collect and process data within …
urbanization. IoT networks allow distributed smart devices to collect and process data within …
Internet of things (IoT) security dataset evolution: Challenges and future directions
The evolution of mobile technologies has introduced smarter and more connected objects
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
into our day-to-day lives. This trend, known as the Internet of Things (IoT), has applications …
An ensemble learning and fog-cloud architecture-driven cyber-attack detection framework for IoMT networks
Abstract Internet of Medical Things (IoMT), an application of Internet of Things (IoT), is
addressing countless limitation of traditional health-care systems such as quality of patient …
addressing countless limitation of traditional health-care systems such as quality of patient …
[HTML][HTML] Advanced feature extraction and selection approach using deep learning and Aquila optimizer for IoT intrusion detection system
Developing cyber security is very necessary and has attracted considerable attention from
academy and industry organizations worldwide. It is also very necessary to provide …
academy and industry organizations worldwide. It is also very necessary to provide …
Graph neural network-driven traffic forecasting for the connected internet of vehicles
Due to great advances in wireless communication, the connected Internet of vehicles
(CIoVs) has become prevalent. Naturally, internal connections among active vehicles are an …
(CIoVs) has become prevalent. Naturally, internal connections among active vehicles are an …
A distributed intrusion detection system to detect DDoS attacks in blockchain-enabled IoT network
Abstract The Internet of Things (IoT) is emerging as a new technology for the development of
various critical applications. However, these applications are still working on centralized …
various critical applications. However, these applications are still working on centralized …
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 …