Improving Performance of Autoencoder-Based Network Anomaly Detection on NSL-KDD Dataset

Improving Performance of Autoencoder-Based Network Anomaly Detection on NSL-KDD Dataset

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 has been a number of Autoencoder (AE) based deep learning approaches for network anomaly detection to improve our pos...

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Bibliographic Details
Main Authors: Wen Xu, Julian Jang-Jaccard, Amardeep Singh, Yuanyuan Wei, Fariza Sabrina
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Network security
intrusion detection systems
network-based IDSs
anomaly detection
NSL-KDD
artificial intelligence
Online Access:https://ieeexplore.ieee.org/document/9552882/

Internet

https://ieeexplore.ieee.org/document/9552882/

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