A method for user authentication performed by a computing device , comprising: capturing by a sensor multiple biometric features relating to an authentication gesture that is performed by a user as a device authentication attempt , wherein the multiple biometric features include one or more touch features, and wherein the multiple biometric features include a relative location feature that reflects geometry of a hand of the user; retrieving stored values of the multiple biometric features for the user obtained during a training session where the user repeatedly performed the authentication gesture ; obtaining a personalized similarity threshold derived from the stored values, the personalized similarity threshold accounting for the user's variability in performing the authentication gesture and how the variability affects individual features of the multiple biometric features ; comparing captured values of the multiple biometric features to the stored values ; evaluating a similarity of the captured values relative to the stored values by employing a similarity metric derived from the stored values, wherein employing the similarity metric comprises generating a weighted sum of differences between captured values and the stored values, wherein a weight, W i , of a feature i represents an importance of the feature for the user to emphasize those features that the user can accurately reproduce across authentication gesture instances, wherein the weight W i is based on the variance and mean of features i across the stored values; authenticating the user on the device if the personalized similarity threshold is satisfied by the result of the evaluation of the similarity; wherein the weight W i is given by: W i = exp − σ F i μ F i where σ F ( i ) and μ F ( i ) is the variance and mean of the values for feature i. capturing by a sensor multiple biometric features relating to an authentication gesture that is performed by a user as a device authentication attempt , wherein the multiple biometric features include one or more touch features, and wherein the multiple biometric features include a relative location feature that reflects geometry of a hand of the user; retrieving stored values of the multiple biometric features for the user obtained during a training session where the user repeatedly performed the authentication gesture ; obtaining a personalized similarity threshold derived from the stored values, the personalized similarity threshold accounting for the user's variability in performing the authentication gesture and how the variability affects individual features of the multiple biometric features ; comparing captured values of the multiple biometric features to the stored values ; evaluating a similarity of the captured values relative to the stored values by employing a similarity metric derived from the stored values, wherein employing the similarity metric comprises generating a weighted sum of differences between captured values and the stored values, wherein a weight, W i , of a feature i represents an importance of the feature for the user to emphasize those features that the user can accurately reproduce across authentication gesture instances, wherein the weight W i is based on the variance and mean of features i across the stored values; <EOS>