Identification of a smartphone user via keystroke analysis

Abstract

Keystroke analysis has been an accepted method for user identification and authentication since the early 1980s. Most of the research in this field of biometrics has focused on traditional computer keyboards, with very few experiments performed on touchscreen keyboards found on modern smartphones. This study focused on identifying a smartphone user based on typing samples input by copying pre-written text, as well as spontaneously-authored free text. Features used for identification were duration of key press, as well as bigram and trigram transitions. User classification based on duration features proved to be successful in 70 percent of inputs to our k-nearest neighbors classifier.