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: 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: 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: 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: 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: 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.

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: An apparatus with a method, and or application, and or service to collect more fine rained or extra event data, that may not be accessible directly by the underlying architecture. This is been done by adding a virtual overlay over selected portion of the screen and detecting events inside or outside of his own context.

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: 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: In detecting the identity of a person currently using a computer (100) and in particular for detecting whether the person is the intended or authorized user of the computer previously established user patterns of users as stored in a database (4) are matched, in comparators (9), with data of the person's interactions through the computer. The interactions are detected by a monitoring module (2) that in testing modules (7) can process data of the interactions and storing them in buffers (8) to be used by the comparators. Such data can include data of interactions that happen directly after each other and can also include one or more time characteristic of each detected interaction.

Abstract: In detecting the identity of a person currently using a computer (100) and in particular for detecting whether the person is the intended or authorized user of the computer previously established user patterns of users as stored in a database (4) are matched, in comparators (9), with data of the person's interactions through the computer. The interactions are detected by a monitoring module (2) that in testing modules (7) can process data of the interactions and storing them in buffers (8) to be used by the comparators. Such data can include data of interactions that happen directly after each other and can also include one or more time characteristic of each detected interaction.