Abstract: A method for determining authenticity of a document is provided that includes receiving, by an electronic device, an image of a document, assigning a label to the image, and obtaining vectors for each image in a subset of images. Each image is of a document and is assigned the same label as the received image. Moreover, the method includes encoding the received image into a vector, calculating a distance between the vector of the received image and each obtained vector, comparing each of the calculated distances against a threshold distance, and calculating a number of the calculated distances that are less than or equal to the threshold distance. In response to determining the calculated number is at least equal to a required number, the document in the received image is determined to be authentic. Otherwise, the received image requires manual review.

Abstract: A method for authenticating a user is provided that includes capturing, by a computing device, key stroke data generated as a result of a user typing content into the computing device, and calculating feature values from the key stroke data. The method also includes calculating distance scores from the feature values and average distance scores from the distance scores, and entering the average distance scores into a classifier. The user is successfully authenticated when the classifier verifies the identity of the user.

Abstract: A method for enhanced liveness detection of facial image data is provided that includes capturing movement data of an electronic device while capturing, using the electronic device, facial image data of a user. In response to determining the captured movement data is consistent with movement data expected to be captured during capture of facial image data, the method includes deciding the captured facial image data is genuine. In response to determining the captured movement data is different than movement data expected to be generated during capture of facial image data, the method includes deciding the captured facial image data is fraudulent.

Abstract: A method for authenticating a user is provided that includes capturing, by a computing device, key stroke data generated as a result of a user typing content into the computing device, and calculating feature values from the key stroke data. The method also includes calculating distance scores from the feature values and average distance scores from the distance scores, and entering the average distance scores into a classifier. The user is successfully authenticated when the classifier verifies the identity of the user.

Abstract: A method identifying a client computer system is provided that includes requesting over a network, by a client computer system, to access a server computer system operating an online service. The client computer system includes an input device. Moreover, the method includes granting access, by the server computer system, to the client computer system, and capturing input data from the client computer system, by the server computer system. The input data is generated by activity of the input device. Furthermore, the method includes calculating temporal differences from the captured input data, a distribution from the temporal differences, and a clustering tendency and a clustering period for the distribution from the captured input data. Additionally, the method includes identifying, by the server computer system, the client computer system when the calculated clustering tendency and clustering period match corresponding data for a client computer system stored in the server computer system.

Abstract: A method identifying a client computer system is provided that includes requesting over a network, by a client computer system, to access a server computer system operating an online service. The client computer system includes an input device. Moreover, the method includes granting access, by the server computer system, to the client computer system, and capturing input data from the client computer system, by the server computer system. The input data is generated by activity of the input device. Furthermore, the method includes calculating temporal differences from the captured input data, a distribution from the temporal differences, and a clustering tendency and a clustering period for the distribution from the captured input data. Additionally, the method includes identifying, by the server computer system, the client computer system when the calculated clustering tendency and clustering period match corresponding data for a client computer system stored in the server computer system.

Abstract: A method for capturing biometric data is provided that includes causing, by a vibration engine included in a computing device, the computing device to vibrate. Moreover, the method includes detecting, by the computing device, movement of the computing device where the movement represents dampened computing device vibrations and capturing, by the computing device, data regarding the movement.