DOC-IDS: A Deep Learning-Based Method for Feature Extraction and Anomaly Detection in Network Traffic

With the growing diversity of cyberattacks in recent years, anomaly-based intrusion detection systems that can detect unknown attacks have attracted significant attention. Furthermore, a wide range of studies on anomaly detection using machine learning and deep learning methods have been conducted....

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Bibliographic Details
Published in:	Sensors Vol. 22; no. 12; p. 4405
Main Authors:	Yoshimura, Naoto, Kuzuno, Hiroki, Shiraishi, Yoshiaki, Morii, Masakatu
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.06.2022 MDPI
Subjects:	Algorithms anomaly detection autoencoder Chemical technology Classification convolutional neural network Datasets Deep learning deep learning; feature extraction; anomaly detection; convolutional neural network; autoencoder; intrusion detection Experiments feature extraction Feature selection intrusion detection Machine Learning Methods Neural networks Neural Networks, Computer Support vector machines TP1-1185 Value engineering
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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