Detecting Unknown Attacks in IoT Environments: An Open Set Classifier for Enhanced Network Intrusion Detection
Author:
Affiliation:
1. Texas A&M University,Clean and Resilient Energy Systems (CARES) Lab,College Station,TX,USA
2. Texas A&M University,Clean and Resilient Energy Systems (CARES) Lab,Galveston,TX,USA
3. Army Cyber Institute,United States Military Academy,NY,USA
Funder
U.S. Military Academy
U.S. Army Combat Capabilities Development Command
Arm
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10356123/10356124/10356319.pdf?arnumber=10356319
Reference25 articles.
1. Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
2. A Novel PCA-Firefly Based XGBoost Classification Model for Intrusion Detection in Networks Using GPU
3. Learning and the Unknown: Surveying Steps toward Open World Recognition
4. Open-set recognition: A good closed-set classifier is all you need?;Vaze,2021
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