Systematically Assessing the Security Risks of AI/ML-enabled Connected Healthcare Systems
Author:
Affiliation:
1. University of British,Columbia
2. National Research Council,Canada
Funder
Natural Sciences and Engineering Research Council of Canada (NSERC)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10614360/10614402/10614410.pdf?arnumber=10614410
Reference64 articles.
1. ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System
2. Detection of Adversarial Attacks against the Hybrid Convolutional Long Short-Term Memory Deep Learning Technique for Healthcare Monitoring Applications
3. Adversarial Attack and Defence through Adversarial Training and Feature Fusion for Diabetic Retinopathy Recognition
4. Adversarial Vulnerability of Deep Learning Models in Analyzing Next Generation Sequencing Data
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