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Found 2 papers, 1 papers with code
Failure-tolerant Distributed Learning for Anomaly Detection in Wireless Networks
When such failures arise in wireless communications networks, important services that they use/provide (like anomaly detection) can be left inoperable and can result in a cascade of security problems.
Defending Regression Learners Against Poisoning Attacks
Regression models, which are widely used from engineering applications to financial forecasting, are vulnerable to targeted malicious attacks such as training data poisoning, through which adversaries can manipulate their predictions.
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