Generative Adversarial Networks for Robust Anomaly Detection in Noisy IoT Environments
Author:
Affiliation:
1. Poly technique Montreal,Department of Computer and Software Engineering,Montreal,QC,Canada
2. Université Laval,Department of Computer Science,Québec,QC,Canada
3. School of Computing, Queen's University,Kingston,ON,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622882.pdf?arnumber=10622882
Reference33 articles.
1. Anatomy of Threats to the Internet of Things
2. A review of industrial big data for decision making in intelligent manufacturing
3. Using IoT technology for computer-integrated manufacturing systems in the semiconductor industry
4. Deep learning-enabled anomaly detection for IoT systems
5. A Survey of Physics-Based Attack Detection in Cyber-Physical Systems
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