# US 2019/0377902 A1 · Systems and Methods for Controlling Data Exposure Using Artificial-Intelligence-Based Modeling > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0377902 A1 - Document ID: US20190377902A1 - Status: Published application - Kind: A1 - Application number: 16/273,877 - Filed: 2019-02-12 - Published: 2019-12-12 - Earliest claimed: 2018-06-11 - Assignees: Grey Market Labs, PBC - Applicants: Grey Market Labs, PBC - Inventors: Kristopher Paul Schroeder; Timothy Ryan Underwood - Web page: https://patentgrep.com/patent/US20190377902A1 ## CPC - G06F 21/6263: {during internet communication, e.g. revealing personal data from cookies} - G06F 21/645: {using a third party} - G06N 20/00: Machine learning - G06N 20/20: Ensemble learning - H04L 63/0414: {during transmission, i.e. party's identity is protected against eavesdropping, e.g. by using temporary identifiers, but is known to the other party or parties involved in the communication} - H04L 63/102: {Entity profiles} - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract Systems and methods for controlling the exposure of data privacy elements are provided to generate an artificial profile model. The artificial profile model may include a constraint for generating new artificial profiles. A signal may be received indicating that a computing device is requesting access to a network location. One or more data privacy elements associated with the computing device can be detected. An artificial profile can be determined for the computing device. The artificial profile may be usable to identify the computing device. The one or more data privacy elements may be automatically modified according to the constraint included in the artificial profile model. The method may include generating a new artificial profile for the computing device. The new artificial profile may include the modified one or more data privacy elements. The new artificial profile may mask the computing device from being identified. ## Claims ### Claim 1 A computer-implemented method, comprising: identifying, at a platform-secured network element between a computing device and a gateway device, a set of data privacy elements, wherein a data privacy element characterizes a feature of a computing device, and wherein a data privacy element is detectable by a network host; generating an artificial profile model, wherein the artificial profile model includes the set of data privacy elements, wherein the artificial profile model defines a relationship, and wherein a relationship can be associated with one or more constraints; receiving a signal indicating that a computing device is requesting access to a network location; detecting one or more data privacy elements associated with the computing device request to access the network location; determining an artificial profile for the computing device, wherein the artificial profile includes the one or more data privacy elements, and wherein the artificial profile is usable to identify the computing device; modifying the one or more data privacy elements, wherein the one or more data privacy elements are modified according to a constraint associated with the relationship defined by the artificial profile model; and generating a new artificial profile for the computing device, wherein the new artificial profile includes the modified one or more data privacy elements, and wherein the new artificial profile masks the computing device from being identified. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the computing device is connectable to the platform-secured network element using a platform-secured browser, and wherein the platform-secured network element includes an application deployed in a cloud network environment. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein the platform-secured network element is a standalone device providing a secured connection point between the computing device and the network location. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, wherein the platform secured-network element is embedded within the computing device, and wherein one or more hardware communication components physically separate a communication of the computing device from other functionalities of the computing device. ### Claim 5 (depends on 1) The computer-implemented method of claim 1, wherein the platform-secured network element is scalable to one or more computing devices in a single location or one or more computing devices in an enterprise network. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein the constraint included in the artificial profile model represents a dependency between two or more data privacy elements of the set of data privacy elements. ### Claim 7 (depends on 1) The computer-implemented method of claim 1, wherein the artificial profile model includes one or more attribution vectors, wherein an attribution vector represents a detectable characteristic associated with the computing device. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the artificial profile model is generated by evaluating the set of data privacy elements using one or more machine-learning techniques, wherein a result of the evaluation is used to determine the constraint for generating new artificial profiles. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, further comprising: modifying the new artificial profile when the computing device requests access to another network location, wherein the new artificial profile is modified according to the constraint included in the artificial model profile. ### Claim 10 A system, comprising: one or more data processors; and a non-transitory computer-readable storage medium containing instructions which, when executed on the one or more data processors, cause the one or more data processors to perform operations including: identifying, at a platform-secured network element between a computing device and a gateway device, a set of data privacy elements, wherein a data privacy element characterizes a feature of a computing device, and wherein a data privacy element is detectable by a network host; generating an artificial profile model, wherein the artificial profile model includes the set of data privacy elements, wherein the artificial profile model defines a relationship, and wherein a relationship can be associated with one or more constraints; receiving a signal indicating that a computing device is requesting access to a network location; detecting one or more data privacy elements associated with the computing device request to access the network location; determining an artificial profile for the computing device, wherein the artificial profile includes the one or more data privacy elements, and wherein the artificial profile is usable to identify the computing device; modifying the one or more data privacy elements, wherein the one or more data privacy elements are modified according to a constraint associated with the relationship defined by the artificial profile model; and generating a new artificial profile for the computing device, wherein the new artificial profile includes the modified one or more data privacy elements, and wherein the new artificial profile masks the computing device from being identified. ### Claim 11 (depends on 10) The system of claim 10, wherein the operations further comprise: identifying an input element included in the network location; receiving input, wherein the input is associated with an input signature; modifying the input signature; and transmitting the input, wherein when the input is received at the network location, the input is associated with the modified input signature. ### Claim 12 (depends on 10) The system of claim 10, wherein the constraint included in the artificial profile model represents a dependency between two or more data privacy elements of the set of data privacy elements. ### Claim 13 (depends on 10) The system of claim 10, wherein modifying the one or more data privacy elements includes preventing the one or more data privacy elements from being exposed to the network host. ### Claim 14 (depends on 10) The system of claim 10, wherein the artificial profile model is generated by evaluating the set of data privacy elements using one or more machine-learning techniques, wherein a result of the evaluation is used to determine the constraint for generating new artificial profiles. ### Claim 15 (depends on 10) The system of claim 10, wherein the operations further comprise: modifying the new artificial profile when the computing device requests access to another network location, wherein the new artificial profile is modified according to the constraint included in the artificial model profile. ### Claim 16 A computer-program product tangibly embodied in a non-transitory machine-readable storage medium, including instructions configured to cause a data processing apparatus to perform operations including: identifying, at a platform-secured network element between a computing device and a gateway device, a set of data privacy elements, wherein a data privacy element characterizes a feature of a computing device, and wherein a data privacy element is detectable by a network host; generating an artificial profile model, wherein the artificial profile model includes the set of data privacy elements, wherein the artificial profile model defines a relationship, and wherein a relationship can be associated with one or more constraints; receiving a signal indicating that a computing device is requesting access to a network location; detecting one or more data privacy elements associated with the computing device request to access the network location; determining an artificial profile for the computing device, wherein the artificial profile includes the one or more data privacy elements, and wherein the artificial profile is usable to identify the computing device; modifying the one or more data privacy elements, wherein the one or more data privacy elements are modified according to a constraint associated with the relationship defined by the artificial profile model; and generating a new artificial profile for the computing device, wherein the new artificial profile includes the modified one or more data privacy elements, and wherein the new artificial profile masks the computing device from being identified. ### Claim 17 (depends on 16) The computer-program product of claim 16, wherein the operations further comprise: identifying an input element included in the network location; receiving input, wherein the input is associated with an input signature; modifying the input signature; and transmitting the input, wherein when the input is received at the network location, the input is associated with the modified input signature. ### Claim 18 (depends on 16) The computer-program product of claim 16, wherein the constraint included in the artificial profile model represents a dependency between two or more data privacy elements of the set of data privacy elements. ### Claim 19 (depends on 16) The computer-program product of claim 16, wherein modifying the one or more data privacy elements includes preventing the one or more data privacy elements from being exposed to the network host. ### Claim 20 (depends on 16) The computer-program product of claim 16, wherein the artificial profile model is generated by evaluating the set of data privacy elements using one or more machine-learning techniques, wherein a result of the evaluation is used to determine the constraint for generating new artificial profiles.