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The Internet contains large amounts of adult content. With only a few taps, or mis-taps, an under-aged user can be exposed to age-inappropriate content. Currently, this can be avoided by creating age-restricted profiles or restricting users to child-friendly applications (apps). However, these existing measures are time-consuming, laborious, and require a higher level of technical literacy than many parents can afford. We believe a better solution is to use a browser or an app that automatically detects the user's age then applies any appropriate content filters. For such a browser/app to be developed, we must learn that age estimation can indeed be performed with an acceptable rate of error. To that end, we created an Android app that collects biometric touchscreen data from elementary school, middle school, high school, and university students. Touch samples were collected from participants aged 5 to 61 on both smartphones and tablets. We focused exclusively on zoom-in and zoom-out touchscreen data samples. We made this decision because we found the zoom gesture to be rich with data and highly used among the most popular applications. Furthermore, we identify a niche within the current research landscape: no other machine learning experiments have leveraged the benefits of the zoom gesture for age estimation. We collected a total of 41,911 zoom data samples. From each zoom sample, 90 features were extracted. Those features were then used to train and test on six regressors and six classifiers to build a method that can accurately estimate the user's age from their touchscreen behavior. The regressors performed with the best mean absolute errors (MAEs) of 2.27 and 2.54 years for smartphones and tablets, respectively. The classifiers performed with the best accuracies of 90% and 91% for smartphones and tablets, respectively. Given these results, it is our belief that not only is touch-based age estimation viable, but developing a child-safe browser or a parental control app with this underlying technology is a worthwhile endeavor. © 2022 Elsevier Ltd

5 citations (Crossref) [2023-10-31]