An anomaly detection algorithm based on ensemble learning for 5G environment
L Lei, L Kou, X Zhan, J Zhang, Y Ren - Sensors, 2022 - mdpi.com
With the advent of the digital information age, new data services such as virtual reality,
industrial Internet, and cloud computing have proliferated in recent years. As a result, it …
industrial Internet, and cloud computing have proliferated in recent years. As a result, it …
A self-adaptive deep learning-based system for anomaly detection in 5G networks
The upcoming fifth-generation (5G) mobile technology, which includes advanced
communication features, is posing new challenges on cybersecurity defense systems …
communication features, is posing new challenges on cybersecurity defense systems …
Design and implementation of an anomaly network traffic detection model integrating temporal and spatial features
With the rapid development and widespread application of cloud computing, cloud
computing open networks and service sharing scenarios have become more complex and …
computing open networks and service sharing scenarios have become more complex and …
EnClass: Ensemble-based classification model for network anomaly detection in massive datasets
With an exponential increase in the Internet traffic over the network, there are growing
concerns of identification of legitimate users which are the bulk sources of Internet traffic …
concerns of identification of legitimate users which are the bulk sources of Internet traffic …
Network traffic anomaly detection based on information gain and deep learning
X Lu, P Liu, J Lin - Proceedings of the 2019 3rd International Conference …, 2019 - dl.acm.org
With the rapid development of the Internet, the network traffic shows an explosive growth
trend. Although the Internet facilitates people's lives, it also brings a lot of security threats …
trend. Although the Internet facilitates people's lives, it also brings a lot of security threats …
Research on anomaly network detection based on self-attention mechanism
W Hu, L Cao, Q Ruan, Q Wu - Sensors, 2023 - mdpi.com
Network traffic anomaly detection is a key step in identifying and preventing network security
threats. This study aims to construct a new deep-learning-based traffic anomaly detection …
threats. This study aims to construct a new deep-learning-based traffic anomaly detection …
Analysis of anomaly detection and identification methods in 5G traffic
Anomaly detection is an important task in 5G technology and many other areas of human
life. In this paper, statistical methods of data analysis, such as survival analysis, time series …
life. In this paper, statistical methods of data analysis, such as survival analysis, time series …
Intelligent anomaly detection for large network traffic with Optimized Deep Clustering (ODC) algorithm
The availability of an enormous amount of unlabeled datasets drives the anomaly detection
research towards unsupervised machine learning algorithms. Deep clustering algorithms for …
research towards unsupervised machine learning algorithms. Deep clustering algorithms for …
Efficient approach for anomaly detection in internet of things traffic using deep learning
The network intrusion detection system (NIDs) is a significant research milestone in
information security. NIDs can scan and analyze the network to detect an attack or anomaly …
information security. NIDs can scan and analyze the network to detect an attack or anomaly …
Deep learning based anomaly detection scheme in software-defined networking
Y Qin, J Wei, W Yang - 2019 20th Asia-Pacific Network …, 2019 - ieeexplore.ieee.org
Software Defined Networking (SDN) has attracted more and more attention due to its
prominent features that are different from the traditional network. SDN is programmable …
prominent features that are different from the traditional network. SDN is programmable …