Method for generating a human likeness score

A non-transitory computer-readable medium storing computer code, which when executed by one or more processors of a compute device, causes the compute device to perform operations comprising:

• receiving a request to determine whether a user attempting to access a service provided by a host compute device is a human or an automated software;
• obtaining an input motion that the user entered while the user solved a challenge-response test for accessing the service;
• extracting a noise component of the input motion, wherein the noise component of the input motion represents oscillations with respect to a smooth input motion;
• retrieving a noise model characterizing noise patterns of input motions previously entered into graphical user interfaces by humans;
• comparing the noise component of the input motion with the noise model;
• calculating a human likeness score of the user based on the comparison of the noise component of the input motion with the noise model, wherein the human likeness score indicates a likelihood that the user is a human as opposed to an automated software;
• determining whether the user is a or an automated software human based on the human likeness score of the user;
• and
• sending a result of the determination of whether the user is a human to the host compute device such that the host compute device can allow or restrict access to the service by the user depending on the result of the determination of whether the user is a human or an automated software.

A computer-implemented method comprising:

• receiving a request to determine whether a user attempting to access a service provided by a host compute device is a human or an automated software;
• obtaining an input motion that the user entered while the user solved a challenge-response test for accessing the service;
• extracting a noise component of the input motion, wherein the noise component of the input motion represents oscillations with respect to a smooth input motion;
• retrieving a noise model characterizing noise patterns of input motions previously entered into graphical user interfaces by humans;
• comparing the noise component of the input motion with the noise model;
• calculating a human likeness score of the user based on the comparison of the noise component of the input motion with the noise model, wherein the human likeness score indicates a likelihood that the user is a human as opposed to an automated software;
• determining whether the user is a human or an automated software based on the human likeness score of the user;
• and
• sending a result of the determination of whether the user is a human or an automated software to the host compute device such that the host compute device can allow or restrict access to the service by the user depending on the result of the determination of whether the user is a human or an automated software.