EVADEML

Our project is focused on understanding, evaluating, and improving the effectiveness of machine learning methods in the presence of motivated and sophisticated adversaries... Machine learning has shown remarkable success in solving complex classification problems, but current machine learning techniques produce models that are vulnerable to adversaries who may wish to confuse them, especially when used for security applications like malware classification... The key assumption of machine learning is that a model that is trained on training data will perform well in deployment because the training data is representative of the data that will be seen when the classifier is deployed.