25.8.2
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CCET - Adversarial Machine Learning Module

Adversarial Machine Learning has profound implications for safety-critical systems that rely on machine learning techniques, like autonomous driving. Machine learning models, such as neural networks, are often not robust to adversarial inputs. This module introduces concepts from machine learning and then discusses how to generate adversarial inputs for assessing robustness of machine learning models. Potential defenses — and their limits — are also discussed.