Autoencoder Optimization for Anomaly Detection: A Comparative Study with Shallow Algorithms-Reference-Cited by-同舟云学术

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Autoencoder Optimization for Anomaly Detection: A Comparative Study with Shallow Algorithms

Published:2024-06-30 Issue: Volume:18 Page:1-8
ISSN:
Container-title:2024 International Joint Conference on Neural Networks (IJCNN)
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Author:

Kumar Vikas¹,Srivastava Vishesh¹,Mahjabin Sadia¹,Pal Arindam¹,Klüttermann Simon¹,Müller Emmanuel¹

Affiliation:

1. TU Dortmund University,Dortmund,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10649807/10649898/10650057.pdf?arnumber=10650057

Reference48 articles.

1. LSTM Autoencoders for IoT Anomaly Detection;Kumar;IEEE Trans. Netw. Serv. Manage,2021

2. Deep Learning for Intrusion Detection in IoT Networks;Li;J. Netw. Secur,2020

3. SDN-ADS: Software-Defined Network-Based Anomaly Detection System for Cloud and Edge Computing;Shah;Int. J. Cloud Comput,2021

4. ANN Models for Anomaly Detection: A Review;Gupta;J. Mach. Learn. Res,2021

5. Deep Residual Learning for Image Recognition

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