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With the growing popularity of smartphones, continuous and implicit authentication of such devices via behavioral biometrics such as touch dynamics becomes an attractive option, especially when the physical biometrics are challenging to utilize, or their frequent and continuous usage annoys the user. However, touch dynamics is vulnerable to potential security attacks such as shoulder surfing, camera attack, and smudge attack. As a result, it is challenging to rule out genuine imposters while only relying on models that learn from real touchstrokes. In this paper, a touchstroke authentication model based on Auxiliary Classifier Generative Adversarial Network (AC-GAN) is presented. Given a small subset of a legitimate user's touchstrokes data during training, the presented AC-GAN model learns to generate a vast amount of synthetic touchstrokes that closely approximate the real touchstrokes, simulating imposter behavior, and then uses both generated and real touchstrokes in discriminating real user from the imposters. The presented network is trained on the Touchanalytics dataset and the discriminability is evaluated with popular performance metrics and loss functions. The evaluation results suggest that it is possible to achieve comparable authentication accuracies with Equal Error Rate ranging from 2% to 11% even when the generative model is challenged with a vast number of synthetic data that effectively simulates an imposter behavior. The use of AC-GAN also diversifies generated samples and stabilizes training. 

In the spring of 2020, the initial surge of COVID-19 infections and deaths was flattened using a combination of economic shutdowns and noneconomic non-pharmaceutical interventions (NPIs). The possibility of a second wave of infections and deaths raises the question of what interventions can be used to significantly reduce deaths while supporting, not preventing, economic recovery. We use a five-age epidemiological model combined with sixty-six-sector economic accounting to examine policies to avert and to respond to a second wave. We find that a second round of economic shutdowns alone are neither sufficient nor necessary to avert or quell a second wave. In contrast, noneconomic NPIs, such as wearing masks and personal distancing, increasing testing and quarantine, reintroducing restrictions on social and recreational gatherings, and enhancing protections for the elderly together can mitigate a second wave while leaving room for an economic recovery.