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A comprehensive review on detection of cyber-attacks: Data sets, methods, challenges, and future research directions
Rapid developments in network technologies and the amount and scope of data transferred
on networks are increasing day by day. Depending on this situation, the density and …
on networks are increasing day by day. Depending on this situation, the density and …
An improved anomaly detection model for IoT security using decision tree and gradient boosting
M Douiba, S Benkirane, A Guezzaz… - The Journal of …, 2023 - Springer
Abstract Internet of Things (IoT) represents a massive deployment of connected, intelligent
devices that communicate directly in private, public, and professional environments without …
devices that communicate directly in private, public, and professional environments without …
M-MultiSVM: An efficient feature selection assisted network intrusion detection system using machine learning
The intrusions are increasing daily, so there is a huge amount of privacy violations, financial
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …
loss, illegal transferring of information, etc. Various forms of intrusion occur in networks, such …
Unsupervised deep learning approach for network intrusion detection combining convolutional autoencoder and one-class SVM
A Binbusayyis, T Vaiyapuri - Applied Intelligence, 2021 - Springer
With the rapid advancement in network technologies, the need for cybersecurity has gained
increasing momentum in recent years. As a primary defense mechanism, an intrusion …
increasing momentum in recent years. As a primary defense mechanism, an intrusion …
Securing mobile edge computing using hybrid deep learning method
In recent years, Mobile Edge Computing (MEC) has revolutionized the landscape of the
telecommunication industry by offering low-latency, high-bandwidth, and real-time …
telecommunication industry by offering low-latency, high-bandwidth, and real-time …
Toward design of an intelligent cyber attack detection system using hybrid feature reduced approach for iot networks
With simple connectivity and fast-growing demand of smart devices and networks, IoT has
become more prone to cyber attacks. In order to detect and prevent cyber attacks in IoT …
become more prone to cyber attacks. In order to detect and prevent cyber attacks in IoT …
I-SiamIDS: an improved Siam-IDS for handling class imbalance in network-based intrusion detection systems
Abstract Network-based Intrusion Detection Systems (NIDSs) identify malicious activities by
analyzing network traffic. NIDSs are trained with the samples of benign and intrusive …
analyzing network traffic. NIDSs are trained with the samples of benign and intrusive …
A smart anomaly-based intrusion detection system for the Internet of Things (IoT) network using GWO–PSO–RF model
Abstract The Internet of Things (IoT) is adding the advancement in the technology for
creating smart environments to facilitate humans for various works. The technological …
creating smart environments to facilitate humans for various works. The technological …
An intrusion identification and prevention for cloud computing: From the perspective of deep learning
As the Internet industry has connected the globe using advancements in computer network
from LAN to Cloud Infrastructure, Fashions and Developments in Internet of Things (IoT) …
from LAN to Cloud Infrastructure, Fashions and Developments in Internet of Things (IoT) …
Anomaly detection model based on gradient boosting and decision tree for IoT environments security
M Douiba, S Benkirane, A Guezzaz… - Journal of Reliable …, 2023 - Springer
Abstract Internet of Things (IoT) refers to the widespread use of distributed intelligent objects
equipped with various components such as captors, activators, and processors that interact …
equipped with various components such as captors, activators, and processors that interact …