Abstract: An apparatus adapted to identify a user based on keystroke dynamics of an input by the user, the apparatus adapted to: execute a first training phase of training a keystroke sample generator to generate negative keystroke samples; execute a second training phase of training a user identification model based at least in part on a plurality of negative keystroke samples generated using the keystroke sample generator; and execute a deployment of the user identification model to authenticate an input sample associated with the user using the trained user identification model.

Abstract: Technologies are presented herein in support of system and methods for user recognition using motion sensor data. Embodiments of the present invention concern a system and method for capturing motion sensor data using motion sensors of a mobile device and characterizing the motion sensor data into features for user recognition. The motion sensor data of a user is collected by the motion sensors of a mobile device in the form of a motion signal. One or more sets of features are extracted from the motion signal and a subset of discriminative features are then selected. The subset of features is analyzed, and a classification score is generated to classify the user as a genuine user or an imposter user.

Abstract: Technologies are presented herein in support of system and methods for user recognition using motion sensor data. Embodiments of the present invention concern a system and method for capturing motion sensor data using motion sensors of a mobile device and characterizing the motion sensor data into features for user recognition. The motion sensor data of a user is collected by the motion sensors of a mobile device in the form of a motion signal. One or more sets of features are extracted from the motion signal and a subset of discriminative features are then selected. The subset of features is analyzed, and a classification score is generated to classify the user as a genuine user or an imposter user.

Abstract: Methods and systems for disentangling discriminative features of a user of a device from motion signals and authenticating a user on a mobile device are provided. In at least one aspect of the methods and systems, each captured motion signal is divided into segments. The segments are then converted into translated segments using one or more trained translation algorithms. The segments and translated segments are then provided to a machine learning system. Discriminative features of the user are then extracted from the segments and translated segments with the processor using the machine learning system that applies one or more feature extraction algorithms.

Abstract: Secure communications are provided between a user computing device and a server computing device. An enrollment request is received from a user computing device that is configured via a distributed client software application, and is processed. The enrollment request is usable to enroll the user computing device in a network and includes an encrypted partial initial biometric vector associated with a user. An authentication request is processed that is subsequently received that includes an encrypted partial second biometric vector and that is associated with a user of the user computing device. A comparison of the encrypted partial initial biometric vector and the encrypted partial second biometric vector is performed, and a value representing the comparison is generated and transmitted to the user computing device. The user computing device is authenticated where the value is above a minimum threshold.

Abstract: Technologies are presented herein in support of system and methods for user recognition using motion sensor data. Embodiments of the present invention concern a system and method for capturing motion sensor data using motion sensors of a mobile device and characterizing the motion sensor data into features for user recognition. The motion sensor data of a user is collected by the motion sensors of a mobile device in the form of a motion signal. One or more sets of features are extracted from the motion signal and a subset of discriminative features are then selected. The subset of features is analyzed, and a classification score is generated to classify the user as a genuine user or an imposter user.

Abstract: Secure communications are provided between a user computing device and a server computing device. An enrollment request is received from a user computing device that is configured via a distributed client software application, and is processed. The enrollment request is usable to enroll the user computing device in a network and includes an encrypted partial initial biometric vector associated with a user. An authentication request is processed that is subsequently received that includes an encrypted partial second biometric vector and that is associated with a user of the user computing device. A comparison of the encrypted partial initial biometric vector and the encrypted partial second biometric vector is performed, and a value representing the comparison is generated and transmitted to the user computing device. The user computing device is authenticated where the value is above a minimum threshold.

Abstract: Secure communications are provided between a user computing device and a server computing device. An enrollment request is received from a user computing device that is configured via a distributed client software application, and is processed. The enrollment request is usable to enroll the user computing device in a network and includes an encrypted partial initial biometric vector associated with a user. An authentication request is processed that is subsequently received that includes an encrypted partial second biometric vector and that is associated with a user of the user computing device. A comparison of the encrypted partial initial biometric vector and the encrypted partial second biometric vector is performed, and a value representing the comparison is generated and transmitted to the user computing device. The user computing device is authenticated where the value is above a minimum threshold.