A Comprehensive Survey on Machine Learning‐Based Intrusion Detection Systems for Secure Communication in Internet of Things
SVN Santhosh Kumar, M Selvi… - Computational …, 2023 - Wiley Online Library
The Internet of Things (IoT) is a distributed system which is made up of the connections of
smart objects (things) that can continuously sense the events in their sensing domain and …
smart objects (things) that can continuously sense the events in their sensing domain and …
A review of recent approaches on wrapper feature selection for intrusion detection
In this paper, we present a review of recent advances in wrapper feature selection
techniques for attack detection and classification, applied in intrusion detection area. Due to …
techniques for attack detection and classification, applied in intrusion detection area. Due to …
Dual-IDS: A bagging-based gradient boosting decision tree model for network anomaly intrusion detection system
The mission of an intrusion detection system (IDS) is to monitor network activities and
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
assess whether or not they are malevolent. Specifically, anomaly-based IDS can discover …
Multi-dimensional feature fusion and stacking ensemble mechanism for network intrusion detection
A robust network intrusion detection system (NIDS) plays an important role in cyberspace
security for protecting confidential systems from potential threats. In real world network, there …
security for protecting confidential systems from potential threats. In real world network, there …
Deep federated learning enhanced secure POI microservices for cyber-physical systems
Z Guo, K Yu, Z Lv, KKR Choo, P Shi… - IEEE Wireless …, 2022 - ieeexplore.ieee.org
An essential consideration in cyber-physical systems (CPS) is the ability to support secure
communication services, such as points of interest (POI) microservices. Existing approaches …
communication services, such as points of interest (POI) microservices. Existing approaches …
A spectrogram image-based network anomaly detection system using deep convolutional neural network
The dynamics of computer networks have changed rapidly over the past few years due to a
tremendous increase in the volume of the connected devices and the corresponding …
tremendous increase in the volume of the connected devices and the corresponding …
A machine learning approach for intrusion detection system on NSL-KDD dataset
I Abrar, Z Ayub, F Masoodi… - … conference on smart …, 2020 - ieeexplore.ieee.org
In the field of Network Security, there is a constant expedition towards the cyber-attacks
which can lead to a destabilized network. Moreover, with unexpected inception and …
which can lead to a destabilized network. Moreover, with unexpected inception and …
A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks
Abstract Sensors in a Wireless Sensor Network (WSN) sense, process, and transmit
information simultaneously. They mainly find applications in agriculture monitoring …
information simultaneously. They mainly find applications in agriculture monitoring …
An energy efficient clustered gravitational and fuzzy based routing algorithm in WSNs
Wireless sensor networks consist of many tiny sensor nodes which are deployed in various
geographical locations for sensing the normal spectacles and also to transmit the collected …
geographical locations for sensing the normal spectacles and also to transmit the collected …
A novel wireless network intrusion detection method based on adaptive synthetic sampling and an improved convolutional neural network
Z Hu, L Wang, L Qi, Y Li, W Yang - IEEE Access, 2020 - ieeexplore.ieee.org
The diversity of network attacks poses severe challenges to intrusion detection systems
(IDSs). Traditional attack recognition methods usually adopt mining data associations to …
(IDSs). Traditional attack recognition methods usually adopt mining data associations to …