CPC G06F 21/31 (2013.01) [G06F 3/0489 (2013.01); G06F 11/3438 (2013.01); G06N 20/00 (2019.01)] | 16 Claims |
1. A method of training a classifier to identify a user of an electronic device including a keyboard having a plurality of keys, the method comprising:
in a training phase:
receiving training key stroke data associated with the user,
a given portion of the training key stroke data having been generated in response to the user interacting with a given key of the plurality of keys used for inputting a predetermined text into the electronic device;
determining based on the given portion of the training key stroke data, a plurality of time intervals including:
a first time interval, during which the given key is pressed;
a plurality of second time intervals between respective moments of pressing the given key and pressing each one of those of the plurality of keys used for inputting the predetermined text;
a plurality of third time intervals between respective moments of releasing the given key and releasing each one of those of the plurality of keys used for inputting the predetermined text;
a plurality of fourth time intervals between respective moments of pressing the given key and releasing each one of those of the plurality of keys used for inputting the predetermined text;
a plurality of fifth time intervals between respective moments of releasing the given key and pressing each one of those of the plurality of keys used for inputting the predetermined text;
determining, for a given one of the plurality of time intervals, based on a plurality of instances of inputting, by the user, the predetermined text, a respective variance value;
ranking the plurality of time intervals in accordance with respective variance values associated therewith, thereby generating a ranked list of time intervals;
selecting from the ranked list of time intervals, a predetermined number of top time intervals having minimum respective variance values for inclusion in a training set of data;
the predetermined number of top time intervals being associated with a user identifier indicative of an association between the predetermined number of top time intervals and the user; and
training based on the training set of data, the classifier to determine if the predetermined text inputted into the electronic device in future has been inputted by the user.
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