Empirical Evaluation of Autoencoder Models for Anomaly Detection in Packet-based NIDS
Author:
Affiliation:
1. University of South Florida,Tampa,FL,USA
2. United States Military Academy,West Point,NY,USA
Funder
U.S. Military Academy
U.S. Army Combat Capabilities Development Command
U.S. Army
U.S. Department of Defense
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10353927/10354085/10354098.pdf?arnumber=10354098
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1. Survey on SDN based network intrusion detection system using machine learning approaches
2. Network intrusion detection system: A systematic study of machine learning and deep learning approaches
3. Building Auto-Encoder Intrusion Detection System based on random forest feature selection
4. Stacked Autoencoder-based Intrusion Detection System to Combat Financial Fraudulent
5. A hybrid Intrusion Detection System based on Sparse autoencoder and Deep Neural Network
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