Pointer movement modelling for entity classification

A non-transitory computer-readable medium having instructions stored thereon that are executable by a server computer system to perform operations comprising:

• tracking, based on pointer movement information identified at a browser rendered at a user interface of a desktop computer, a sequence of pointer movements, wherein the pointer movement information is transmitted from the desktop computer to the server computer system;
• mapping, based on coordinate locations of pointer movements in the sequence of pointer movements, respective movements in the sequence to a plurality of functional areas;
• generating a movement graph based on the mapping, wherein the generating includes:
• assigning graph nodes to respective functional areas included in the plurality of functional areas;
• and
• assigning graph edges to respective pointer movements in the sequence of pointer movements between respective functional areas included in the plurality of functional areas;
• determining, based on output of the movement graph, whether an entity associated with the sequence of pointer movements is an automated computer;
• in response to receiving a request to authorize an action at the desktop computer, generating an authorization decision for the action based on the determining;
• and
• transmitting, to the desktop computer, the authorization decision.

A system, comprising:

• at least one processor;
• and
• a memory having instructions stored thereon that are executable by the at least one processor to cause the system to:
• track, at a user interface of a mobile device, a sequence of pointer movements, wherein the tracking is based on pointer movement information determined at a mobile application rendered via the user interface of the mobile device and transmitted from the mobile device to the system;
• generate, based on the sequence of pointer movements, a movement graph, wherein the generating includes:
• mapping, based on coordinate locations of pointer movements in the sequence of pointer movements, respective movements in the sequence to a plurality of functional areas;
• assigning graph nodes to respective functional areas included in the plurality of functional areas;
• and
• assigning graph edges to respective pointer movements in the sequence of pointer movements between respective functional areas included in the plurality of functional areas, wherein weights assigned to graph edges are based on a number of pointer movements between pairs of functional areas;
• input the movement graph into a first machine learning model;
• generate, based on output of the first machine learning model, a representative set of pointer movement data;
• input the representative set of pointer movement data into a second, different machine learning model;
• determine, based on output of the second, different machine learning model, whether an entity associated with the sequence of pointer movements is an automated computer;
• in response to receiving a request to authorize an action at the mobile device, generate, based on the determining, an authorization decision for the action;
• and
• transmit, to the mobile device, the authorization decision.