31results about How to "Effective and efficient and scalable and convenient solution" patented technology

A vehicle computing platform may receive driver sensor data indicating whether a driver seat in a vehicle is occupied. The vehicle computing platform may determine, based on the driver sensor data, an identity of a driver of the vehicle. The vehicle computing platform may receive passenger sensor data indicating whether a passenger seat in the vehicle is occupied. The vehicle computing platform may, based on the passenger sensor data indicating that the passenger seat in the vehicle is occupied, obscure information on a screen of the vehicle.

A system for creating a synthetic voice identifier may include a plurality of synthesized voice authorization (SVA) devices and a biometric combinatory device (BCD). The SVAs may be communicatively coupled to the BCD via a network and may communicate utilizing a markup language. The SVA devices may capture an audio signal of a voice of a user, modify the audio signal with a randomized audio frequency signal to generate a modified audio signal, and communicate, the modified audio signal as a synthesized voice signal associated with the user. The BCD may receive biometric information corresponding to a user, the biometric information comprising at least audio information associated with a voice of the user, receive, at an integration module, location information corresponding to a location of the user, combine, the location information and audio signal information associated with the user to generate a synthesized voice identifier associated with the user, and communicate the synthesized voice identifier to a remote device for use in an authentication process of the user.

A system for creating a synthetic voice identifier may include a plurality of synthesized voice authorization (SVA) devices and a biometric combinatory device (BCD). The SVAs may be communicatively coupled to the BCD via a network and may communicate utilizing a markup language. The SVA devices may capture an audio signal of a voice of a user, modify the audio signal with a randomized audio frequency signal to generate a modified audio signal, and communicate, the modified audio signal as a synthesized voice signal associated with the user. The BCD may receive biometric information corresponding to a user, the biometric information comprising at least audio information associated with a voice of the user, receive, at an integration module, location information corresponding to a location of the user, combine, the location information and audio signal information associated with the user to generate a synthesized voice identifier associated with the user, and communicate the synthesized voice identifier to a remote device for use in an authentication process of the user.

Aspects of the disclosure relate to resource allocation and rebating during in-flight data masking and on-demand encryption of big data on a network. Computer machine(s), cluster managers, nodes, and / or multilevel platforms can request, receive, and / or authenticate requests for a big data dataset, containing sensitive and non-sensitive data. Profiles can be auto provisioned, and access rights can be assigned. Server configuration and data connection properties can be defined. Secure connection(s) to the data store can be established. Sensitive information can be redacted into a sanitized dataset based on one or more data obfuscation types. State point information for previously reached safe points can be stored and progressively released such that only the incomplete portion(s) of task(s) need to be resubmitted. The encrypted data can be transmitted, in response to the request, to a source, a target, and / or another computer machine and can be decrypted back into the sanitized dataset.

Aspects of the disclosure relate to resource allocation and rebating during in-flight data masking and on-demand encryption of big data on a network. Computer machine(s), cluster managers, nodes, and / or multilevel platforms can request, receive, and / or authenticate requests for a big data dataset, containing sensitive and non-sensitive data. Profiles can be auto provisioned, and access rights can be assigned. Server configuration and data connection properties can be defined. Secure connection(s) to the data store can be established. Sensitive information can be redacted into a sanitized dataset based on one or more data obfuscation types. RAM requirements and current RAM allocation can be diagnosed. Portion(s) of the current RAM allocation exceeding the RAM requirements can be rebated. The encrypted data can be transmitted, in response to the request, to a source, a target, and / or another computer machine and can be decrypted back into the sanitized dataset.

Aspects of the disclosure relate to information security by identifying unique or related factors in common between individuals subject to a common threat vector. Data mining and data acquisition of public and non-public user information is performed to prevent, disrupt, and / or address criminal, cyber, and fraudulent threats. The information can be normalized into template(s) to align information across disparate datasets and enable efficient storage of the big data into appropriate fields to be tracked. The information can be stored in data warehouse(s) or in multidimensional data structure(s) for investigation if a threat vector against a group of individuals is detected. The multidimensional data can be analyzed to identify direct connections, common connecting entities, and / or connectivity clusters between individuals who were attacked or who may be attacked in the future. Remediation, machine learning, enhanced security, and / or vulnerability assessments may be implemented based on the results of the analysis.