Abstract: Disclosed is a method for continuously authenticating a user based on motion input data. The method includes recording motion input data from a keyboard such as starting coordinates, ending coordinates, and timestamps of key-up actions to determine that a key has been pressed, recording a timestamp of motion input at the starting coordinate, mapping the timestamp of said motion input at the starting coordinate to a key-down action for the key press, determining which key of said virtual keyboard said key-down action refers to, and granting or denying access to a device if the timing of the key which was pressed and released in the key-down action and the corresponding key-up action matches the press and flight timing of a key which was pressed and released in a previously-recorded key-down action and a previously-recorded key-up action.

Abstract: A user accessing data from a server in an authenticated session is determined to be human, an authorized bot, or a non-authorized bot based on receipt of behaviometric information from the user's interactions and responses to and with the server. The user is then denied or granted continued access to receive data, such as financial data, after it is determined if the user is authorized to do so by way of comparing the behaviometric data to known prior behaviometric data for particular humans and bots in embodiments of the disclosed technology.

Abstract: Method for a secure authenticating of a user identity of a device for a service during a session including a transaction between an authentication-client and a connected authentication-server, whereby said authentication-client is running on said device using a user-agent with a specific authentication-interface to communicate encrypted authentication messages using a Transport Layer Security (TLS) protocol between said user-agent of said authentication-client and a web-server of both said authentication-server of a ‘Relying Party’ using a unique and secret authentication-identifier (e.g. a hash-value created from ‘Relying Party’, date and time) between them, and a Behaviometric-server using a unique and secret Behaviometric-identifier (e.g. a hash-value created from a Behaviometric-Server, date and time) between them, whereby said session comprising an earlier authentication stage and at least in authentication case (said user identity is positively authenticated) a later controlling stage.

Abstract: A computer-implemented method, computer device and computer system for detecting multiple users based on a biometric user profile and/or a behavioral user profile.

Abstract: Two user-authenticated sessions are compared between two different servers or users of two different financial institutions. Based on comparisons of sanitized key press timings, position or motion-related inputs, and other inputs it is determined that the sessions were/are with a same user. When this user is identified as a fraudulent actor or malfeasant with one server or banking institution, this data is shared, without sharing confidential information, with the other server or financial institution so that despite a lack of identifying the user himself/herself, the second server or financial institution can modify data sent to this user to prevent fraud and unauthorized access to data of another.

Abstract: Detecting unauthorized access to a device is detected in embodiments of the disclosed technology. After downloading a webpage, code is executed in a browser to scan network ports and determine which ports are open. Further webpage content sent from a web server is determined and/or modified in embodiments of the disclosed technology based on which ports are open. In some embodiments, when a particular port or ports are already in use it is determined that a malfeasant actor has access to the end user device and as such, sensitive data or secure data which is intended for a specific user is no longer sent to the end user device.

Abstract: A computer-implemented method, program-code, web-client device and computer system to realize and guard over a secure input routine based on their behavior.

Abstract: Method for a secure authenticating of a user identity of a device for a service during a session including a transaction between an authentication-client and a connected authentication-server, whereby said authentication-client is running on said device using a user-agent with a specific authentication-interface to communicate encrypted authentication messages using a Transport Layer Security (TLS) protocol between said user-agent of said authentication-client and a web-server of both said authentication-server of a ‘Relying Party’ using a unique and secret authentication-identifier (e.g. a hash-value created from ‘Relying Party’, date and time) between them, and a Behaviometric-server using a unique and secret Behaviometric-identifier (e.g. a hash-value created from a Behaviometric-Server, date and time) between them, whereby said session comprising an earlier authentication stage and at least in authentication case (said user identity is positively authenticated) a later controlling stage.

Abstract: A computer-implemented method for secure authentication of a user to a service for executing a transaction, the method being implemented in a system including a user device including a FIDO-client, a FIDO-server of a relying party providing the service, a behaviometric server and a web server associated with the relying party, the method including a preparation stage and an authentication stage. In the preparation stage a TLS-connection is established between the user device and the web-server, behavioral input data is collected from user device, and a transaction initiation message is transmitted to the behaviometric server. In the authentication stage, behaviometric data received in the transaction initiation message is compared to a second set of behaviometric data to determine whether the data matches, and if the data matches, the transaction is authenticated by the FIDO server.

Abstract: A computer-implemented method, computer program product, and system for determining whether a user exhibits machine behavior, or does not exhibit human-like behavior, thereby to authenticate the user for access to a software service.

Abstract: A method and a corresponding device for authenticating a user for access to protected information, the method comprising generating a behavioral user profile associated with a first user known to be a legitimate user of the protected information, obtaining from a second user, using a behavioral input device associated with a second computing device, a behavioral user sample, storing the behavioral user sample, associated with the second user, in a temporary user profile, comparing the behavioral user sample of the second user to the behavioral user profile, and if the behavioral user sample does not match the behavioral user profile contacting the legitimate first user and receiving from the legitimate first user information regarding the legitimacy of the second user and based on the information received from the first user, providing a response to the second user and updating the user profile.

Abstract: Securely authenticating a user of a device for a service during a session including a transaction between a client and a connected server connected to a Behaviometric-server.

Abstract: A computer-implemented method, computer device and computer system for detecting multiple users based on a biometric user profile and/or a behavioral user profile.

Abstract: Recording, analyzing and categorizing of user interface input via touchpad, touch screens or any device that can synthesize gestures from touch and pressure into input events. Such as, but not limited to, smart phones, touch pads and tablets. Humans may generate the input. The analysis of data may include statistical profiling of individual users as well as groups of users, the profiles can be stored in, but not limited to data containers such as files, secure storage, smart cards, databases, off device, in the cloud etc. A profile may be built from user/users behavior categorized into quantified types of behavior and/or gestures. The profile might be stored anonymized. The analysis may take place in real time or as post processing. Profiles can be compared against each other by all the types of quantified behaviors or by a select few.

Abstract: A method and a corresponding device for authenticating a user for access to protected information, including at a registration stage, generating a biometric user profile and a behavioral user profile associated with a user to be authenticated, and an authenticating stage, obtaining from the user a biometric user sample and a behavioral user sample, comparing the biometric user sample and the behavioral user sample to the biometric user profile and to the biometric behavioral profile associated with the user, and if the biometric user sample and the behavioral user sample match the biometric user profile and the biometric behavioral profile, respectively, enabling the user to access the protected information.

Abstract: A method and a corresponding device for authenticating a user for access to protected information, the method comprising generating a behavioral user profile associated with a first user known to be a legitimate user of the protected information, obtaining from a second user, using a behavioral input device associated with a second computing device, a behavioral user sample, storing the behavioral user sample, associated with the second user, in a temporary user profile, comparing the behavioral user sample of the second user to the behavioral user profile, and if the behavioral user sample does not match the behavioral user profile contacting the legitimate first user and receiving from the legitimate first user information regarding the legitimacy of the second user and based on the information received from the first user, providing a response to the second user and updating the user profile.

Abstract: Estimation of gyroscopic data on a mobile device is determined based on receiving a plurality of magnetometer-angle vectors from a magnetometer and receiving a plurality of accelerometer-angle vectors from an accelerometer. A plurality of matrices transform a coordinate system of the mobile device to an Earth coordinate system based on the magnetometer-angle vectors and the accelerometer-angle vectors. A plurality of estimated gyroscope vectors are then determined based on the plurality of matrices. A computer-implemented method), a program-code, and program-product, and devices for producing same are further disclosed herein.

Abstract: Recording, analyzing and categorizing of user interface input via touchpad, touch screens or any device that can synthesize gestures from touch and pressure into input events. Such as, but not limited to, smart phones, touch pads and tablets. Humans may generate the input. The analysis of data may include statistical profiling of individual users as well as groups of users, the profiles can be stored in, but not limited to data containers such as files, secure storage, smart cards, databases, off device, in the cloud etc. A profile may be built from user/users behavior categorized into quantified types of behavior and/or gestures. The profile might be stored anonymized. The analysis may take place in real time or as post processing. Profiles can be compared against each other by all the types of quantified behaviors or by a select few.

Abstract: A computer-implemented method, computer program product, and system for determining whether a user exhibits machine behavior, or does not exhibit human-like behavior, thereby to authenticate the user for access to a software service.

Abstract: Recording, analyzing and categorizing of user interface input via touchpad, touch screens or any device that can synthesize gestures from touch and pressure into input events. Such as, but not limited to, smart phones, touch pads and tablets. Humans may generate the input. The analysis of data may include statistical profiling of individual users as well as groups of users, the profiles can be stored in, but not limited to data containers such as files, secure storage, smart cards, databases, off device, in the cloud etc. A profile may be built from user/users behavior categorized into quantified types of behavior and/or gestures. The profile might be stored anonymized. The analysis may take place in real time or as post processing. Profiles can be compared against each other by all the types of quantified behaviors or by a select few.