Clustering-based label estimation for network anomaly detection
Sign Up to like & getrecommendations! Published in 2020 at "Digital Communications and Networks"
DOI: 10.1016/j.dcan.2020.06.001
Abstract: Abstract A substantial body of work has been done to identify network anomalies using supervised and unsupervised learning techniques with their unique strengths and weaknesses. In this work, we propose a new approach that takes… read more here.
Keywords: network; clustering based; estimated labels; network anomaly ... See more keywords
NADS-RA: Network Anomaly Detection Scheme Based on Feature Representation and Data Augmentation
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3040510
Abstract: Network anomaly detection aims to identify network anomalies, and it has obtained many achievements using the supervised classification technique. Since the supervised classifier depends on the prior data, it is difficult to accurately classify the… read more here.
Keywords: feature; network anomaly; augmentation; data augmentation ... See more keywords
A Deep Spiking Neural Network Anomaly Detection Method
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/6391750
Abstract: Cyber-attacks on specialized industrial control systems are increasing in frequency and sophistication, which means stronger countermeasures need to be implemented, requiring the designers of the equipment in question to re-evaluate and redefine their methods for… read more here.
Keywords: neural network; deep spiking; spiking neural; anomaly detection ... See more keywords