An Anomaly Detection Model Based On Deep Auto-Encoder and Capsule Graph Convolution via Sparrow Search Algorithm in 6G Internet-of-Everything

S Yin, H Li, AA Laghari, TR Gadekallu… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In recent years, driven by the continuous development of mobile Internet technology and
artificial intelligence technology, the improvement of the manufacturing level of 6G Internet …

Full graph autoencoder for one-class group anomaly detection of IIoT system

Y Feng, J Chen, Z Liu, H Lv… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
With the increasing automation and integration of equipment, it is urgent to carry out
anomaly detection (AD) for the large-scale system to ensure security, in virtue of Industrial …

Analysis of anomaly detection method for Internet of things based on deep learning

W Ma - Transactions on Emerging Telecommunications …, 2020 - Wiley Online Library
With the rapid development of the Internet of things technology, the connection between
things and people is realized in a real sense, and the intelligent perception, recognition, and …

Autoencoder-based network anomaly detection

Z Chen, CK Yeo, BS Lee, CT Lau - 2018 Wireless …, 2018 - ieeexplore.ieee.org
Anomaly detection is critical given the raft of cyber attacks in the wireless communications
these days. It is thus a challenging task to determine network anomaly more accurately. In …

Improving performance of autoencoder-based network anomaly detection on nsl-kdd dataset

W Xu, J Jang-Jaccard, A Singh, Y Wei… - IEEE Access, 2021 - ieeexplore.ieee.org
Network anomaly detection plays a crucial role as it provides an effective mechanism to
block or stop cyberattacks. With the recent advancement of Artificial Intelligence (AI), there …

Network anomaly detection using federated learning and transfer learning

Y Zhao, J Chen, Q Guo, J Teng, D Wu - … on Security and Privacy in Digital …, 2020 - Springer
Since deep neural networks can learn data representation from training data automatically,
deep learning methods are widely used in the network anomaly detection. However …

[HTML][HTML] 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 …

AdaGUM: An Adaptive Graph Updating Model‐Based Anomaly Detection Method for Edge Computing Environment

X Yu, C Shan, J Bian, X Yang, Y Chen… - Security and …, 2021 - Wiley Online Library
With the rapid development of Internet of Things (IoT), massive sensor data are being
generated by the sensors deployed everywhere at an unprecedented rate. As the number of …

Unsupervised and ensemble-based anomaly detection method for network security

D Yang, M Hwang - … on Knowledge and Smart Technology (KST …, 2022 - ieeexplore.ieee.org
Bigdata and IoT technologies are developing rapidly. Accordingly, consideration of network
security is also emphasized, and efficient intrusion detection technology is required for …

CRND: an unsupervised learning method to detect network anomaly

YZ Qu, HL Ma, YM Jiang - Security and Communication …, 2022 - Wiley Online Library
Network anomaly detection system (NADS) is one of the most important methods to maintain
network system security. At present, network anomaly detection models based on deep …