IGRF-RFE: a hybrid feature selection method for MLP-based network intrusion detection on UNSW-NB15 dataset
The effectiveness of machine learning models can be significantly averse to redundant and
irrelevant features present in the large dataset which can cause drastic performance …
irrelevant features present in the large dataset which can cause drastic performance …
Machine-learning-based DDoS attack detection using mutual information and random forest feature importance method
Cloud computing facilitates the users with on-demand services over the Internet. The
services are accessible from anywhere at any time. Despite the valuable services, the …
services are accessible from anywhere at any time. Despite the valuable services, the …
A new DDoS attacks intrusion detection model based on deep learning for cybersecurity
The data is exposed to many attacks during communication in the network environment. It is
becoming increasingly essential to identify intrusions into network communications …
becoming increasingly essential to identify intrusions into network communications …
LSTM-autoencoder-based anomaly detection for indoor air quality time-series data
Anomaly detection for indoor air quality (IAQ) data has become an important area of
research as the quality of air is closely related to human health and well-being. However …
research as the quality of air is closely related to human health and well-being. However …
An efficient hybrid-dnn for ddos detection and classification in software-defined iiot networks
Software-defined networking (SDN)-based Industrial Internet of Things (IIoT) networks have
a centralized controller that is a single attractive target for unauthorized users to attack …
a centralized controller that is a single attractive target for unauthorized users to attack …
A few-shot meta-learning based siamese neural network using entropy features for ransomware classification
Ransomware defense solutions that can quickly detect and classify different ransomware
classes to formulate rapid response plans have been in high demand in recent years …
classes to formulate rapid response plans have been in high demand in recent years …
Robust detection of unknown DoS/DDoS attacks in IoT networks using a hybrid learning model
The fourth industrial revolution is marked by the rapid growth of Internet of Things (IoT)
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …
technology, leading to an increase in the number of IoT devices. Unfortunately, this also …
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 …
DDoS attack detection and mitigation using deep neural network in SDN environment
In the contemporary digital landscape, the escalating threat landscape of cyber attacks,
particularly distributed denial-of-service (DDoS) attacks, has become a paramount concern …
particularly distributed denial-of-service (DDoS) attacks, has become a paramount concern …
Artificial intelligence-enabled DDoS detection for blockchain-based smart transport systems
A smart public transport system is expected to be an integral part of our human lives to
improve our mobility and reduce the effect of our carbon footprint. The safety and ongoing …
improve our mobility and reduce the effect of our carbon footprint. The safety and ongoing …