ROAST selectively trains anomaly detectors on less vulnerable patient data with targeted outlier exposure, boosting recall by 16.2% in black-box settings and reducing training time by 88.3%.
Adversarial examples—security threats to covid-19 deep learning systems in medical iot devices.IEEE Internet of Things Journal, 8(12):9603–9610, 2020
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ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks
ROAST selectively trains anomaly detectors on less vulnerable patient data with targeted outlier exposure, boosting recall by 16.2% in black-box settings and reducing training time by 88.3%.