In a display system according to the present disclosure, a server device includes an authentication processor that authenticates a user for use of a file, based on authentication information of the user input at a user terminal and an access information generator that generates first access information for accessing the file if the user is authenticated by the authentication processor for use of the file, and a display device includes a file acquirer that acquires the file from the server device, based on the first access information generated by the access information generator, and a display processor that displays the file acquired by the file acquirer, on the display.

A method implemented on a visual computing device to authenticate one or more users includes receiving a first three-dimensional pattern from a user. The first three-dimensional pattern is sent to a server computer. At a time of user authentication, a second three-dimensional pattern is received from the user. The second three-dimensional pattern is sent to the server computer. An indication is received from the server computer as to whether the first three-dimensional pattern matches the second three-dimensional pattern within a margin of error. When the first three-dimensional pattern matches the second three-dimensional pattern within the margin of error, the user is authenticated at the server computer. When the first three-dimensional pattern does not match the second three-dimensional pattern within the margin of error, user is prevented from being authenticated at the server computer.

A method implemented on a visual computing device to authenticate one or more users includes receiving a first three-dimensional pattern from a user. The first three-dimensional pattern is sent to a server computer. At a time of user authentication, a second three-dimensional pattern is received from the user. The second three-dimensional pattern is sent to the server computer. An indication is received from the server computer as to whether the first three-dimensional pattern matches the second three-dimensional pattern within a margin of error. When the first three-dimensional pattern matches the second three-dimensional pattern within the margin of error, the user is authenticated at the server computer. When the first three-dimensional pattern does not match the second three-dimensional pattern within the margin of error, user is prevented from being authenticated at the server computer.

Systems and methods for authenticating identification information are disclosed. For example, a system may include an Automated Teller Machine (ATM). An ATM may comprise a user interface. The user interface may comprise a joystick. The user interface may be configured to receive joystick input from a user. The ATM may comprise at least one memory storing instructions. The ATM may comprise at least one processor configured to execute the instructions to perform operations. The operations may comprise receiving identification information from the user. The operations may comprise receiving the joystick input. The operations may comprise extracting a joystick sequence from the joystick input. When the joystick sequence is within a predetermined threshold from a stored joystick sequence corresponding to the identification information, the operations may comprise authenticating the user for an ATM operation.

Human interaction with a webpage may be determined by processing an event stream generated by the client device during the webpage interaction. A classification server receives the event stream and compares components of the event stream, including components of an event header message, with prerecorded datasets. The datasets include prerecorded event streams having a known interaction type. Training clients may be provided for generating the prerecorded datasets.

Human interaction with a webpage may be determined by processing an event stream generated by the client device during the webpage interaction. A classification server receives the event stream and compares components of the event stream, including components of an event header message, with prerecorded datasets. The datasets include prerecorded event streams having a known interaction type. Training clients may be provided for generating the prerecorded datasets.

Embodiments of the present invention relate to password authentication. According to an embodiment of the present invention, a password associated with a user identification is received from a user device. The password is authenticated based on a preset relationship between a seed password and a graphical password associated with the user identification. The seed password consists of a string of characters. The graphical password is a directed path traversing all keys of a keypad in an order. Each of the keys represents one of the characters and is associated with an order number according to the order of the keys being traversed. The preset relationship is that the password consists of respective order numbers associated with respective keys representing corresponding characters of the seed password.

Embodiments of the present invention relate to password authentication. According to an embodiment of the present invention, a password associated with a user identification is received from a user device. The password is authenticated based on a preset relationship between a seed password and a graphical password associated with the user identification. The seed password consists of a string of characters. The graphical password is a directed path traversing all keys of a keypad in an order. Each of the keys represents one of the characters and is associated with an order number according to the order of the keys being traversed. The preset relationship is that the password consists of respective order numbers associated with respective keys representing corresponding characters of the seed password.

Methods and systems disclosed herein describe using machine learning to lock and unlock a device. Machine learning may be trained to recognize one or more features. Once the device has been trained to recognize one or more features, a user may define an unlock condition for the device using the one or more trained features. After defining the unlock condition, the device may be locked by verifying the one or more features that the user defined as the unlock condition using machine learning. When verification is successful, the device may be unlocked and the user allowed to access the device.

Methods and systems disclosed herein describe using machine learning to lock and unlock a device. Machine learning may be trained to recognize one or more features. Once the device has been trained to recognize one or more features, a user may define an unlock condition for the device using the one or more trained features. After defining the unlock condition, the device may be locked by verifying the one or more features that the user defined as the unlock condition using machine learning. When verification is successful, the device may be unlocked and the user allowed to access the device.