How Bad Data Alters Machine Learning Results

The challenge is in creating a deep learning model to detect forms of malware that don't yet exist. In current machine learning research, accuracy estimates don't consider how systems will process future data. "If researchers forget to focus on sensitivity testing and time decay, our models are liable to fail catastrophically in the wild," she explains. This analysis will include a deep learning model designed to detect malicious URLs, which was trained and tested using three sources of URL data.