[HTML][HTML] Machine learning-based anomaly detection in NFV: A comprehensive survey
Network function virtualization (NFV) is a rapidly growing technology that enables the
virtualization of traditional network hardware components, offering benefits such as cost …
virtualization of traditional network hardware components, offering benefits such as cost …
Anomaly and intrusion detection using deep learning for software-defined networks: A survey
VG da Silva Ruffo, DMB Lent, M Komarchesqui… - Expert Systems with …, 2024 - Elsevier
Abstract Software-Defined Networks (SDN) represent an adaptable paradigm for dealing
with network users' dynamic demands. Confidentiality, integrity, and availability are …
with network users' dynamic demands. Confidentiality, integrity, and availability are …
Efficient intrusion detection toward IoT networks using cloud–edge collaboration
Abstract The Internet of Things (IoT) is increasingly utilized in daily life and industrial
production, particularly in critical infrastructures. IoT cybersecurity has an effect on people's …
production, particularly in critical infrastructures. IoT cybersecurity has an effect on people's …
A cognitive security framework for detecting intrusions in IoT and 5G utilizing deep learning
The fast growth of Internet of Things (IoT) gadgets and 5G networks has increased linkage
and accessibility. However, growing interconnectivity poses new threat levels in these …
and accessibility. However, growing interconnectivity poses new threat levels in these …
Real-time clustering based on deep embeddings for threat detection in 6G networks
Trials and deployments of sixth Generation (6G) wireless networks, delivering extreme
capacity, reliability, and efficiency, are expected as early as 2030. Attempts from both …
capacity, reliability, and efficiency, are expected as early as 2030. Attempts from both …
[HTML][HTML] A multi-information fusion anomaly detection model based on convolutional neural networks and AutoEncoder
Z Zhao, H Guo, Y Wang - Scientific Reports, 2024 - nature.com
Network traffic anomaly detection, as an effective analysis method for network security, can
identify differentiated traffic information and provide secure operation in complex and …
identify differentiated traffic information and provide secure operation in complex and …
[HTML][HTML] Dimensionality reduction for images of IoT using machine learning
I Ali, K Wassif, H Bayomi - Scientific Reports, 2024 - nature.com
Sensors, wearables, mobile devices, and other Internet of Things (IoT) devices are
becoming increasingly integrated into all aspects of our lives. They are capable of gathering …
becoming increasingly integrated into all aspects of our lives. They are capable of gathering …
An Avant-Garde African Vulture Optimization (A2VO) based Deep RNN-LSTM Model for 5G-IoT Security
G Ramasubramanian… - Journal of Advanced …, 2023 - semarakilmu.com.my
In current days, 5G is more essential for the Internet of Things (IoT) systems, since it offers a
quicker network with more capacity to address communication needs. The frequency range …
quicker network with more capacity to address communication needs. The frequency range …
Network Intrusion Detection using Deep Convolution Neural Network
In recent years, with the rise of cyber attacks, intrusion detection systems (IDS) have become
an essential component of network security. Deep learning-based approaches have shown …
an essential component of network security. Deep learning-based approaches have shown …
FEDSA-ResnetV2: An Efficient Intrusion Detection System for Vehicle Road Cooperation Based on Federated Learning
Z Qu, Z Cai - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Federated learning (FL)-based intrusion detection systems (IDSs) for vehicle road
cooperation have attracted significant attention in recent years. However, the non …
cooperation have attracted significant attention in recent years. However, the non …