# US 2022/0045841 A1 · Homomorphic technology > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2022/0045841 A1 - Document ID: US20220045841A1 - Status: Published application - Kind: A1 - Application number: 17/497,161 - Filed: 2021-10-08 - Published: 2022-02-10 - Earliest claimed: 2019-12-10 - Assignees: Winkk, Inc. - Applicants: Winkk, Inc - Inventors: Robert O. Keith, JR. - Web page: https://patentgrep.com/patent/US20220045841A1 ## CPC - G06F 21/316: {by observing the pattern of computer usage, e.g. typical user behaviour} - H04L 9/008: {involving homomorphic encryption} - G06F 16/245: Query processing - G06F 16/285: {Clustering or classification} - G06F 21/32: using biometric data, e.g. fingerprints, iris scans or voiceprints - G06F 21/35: communicating wirelessly - G06F 21/43: wireless channels - G06F 21/606: {by securing the transmission between two devices or processes} - G06F 21/6245: {Protecting personal data, e.g. for financial or medical purposes} - G06V 40/1365: {Matching; Classification} - G06V 40/172: {Classification, e.g. identification} - G06V 40/197: {Matching; Classification} - G06V 40/20: Movements or behaviour, e.g. gesture recognition (recognition of facial expressions G06V40/16) - G06V 40/70: Multimodal biometrics, e.g. combining information from different biometric modalities - H04L 9/3231: {Biological data, e.g. fingerprint, voice or retina (network architectures or network communication protocols for supporting authentication of entities using biometrical features in a packet data network H04L63/0861)} - H04L 63/0807: {using tickets, e.g. Kerberos (cryptographic mechanisms or cryptographic arrangements for entity authentication using tickets or tokens H04L9/3213)} - H04L 63/0861: {using biometrical features, e.g. fingerprint, retina-scan (cryptographic mechanisms or cryptographic arrangements for entity authentication using biological data H04L9/3231)} - G06V 40/15: {Biometric patterns based on physiological signals, e.g. heartbeat, blood flow} - H04L 2463/082: applying multi-factor authentication - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A security platform architecture is described herein. A user identity platform architecture which uses a multitude of biometric analytics to create an identity token unique to an individual human. This token is derived on biometric factors like human behaviors, motion analytics, human physical characteristics like facial patterns, voice recognition prints, usage of device patterns, user location actions and other human behaviors which can derive a token or be used as a dynamic password identifying the unique individual with high calculated confidence. Because of the dynamic nature and the many different factors, this method is extremely difficult to spoof or hack by malicious actors or malware software. The data is recorded in a highly secure manner. The data is stored encrypted in a database and accessed using a homomorphic access technology where the actual encrypted contents are not exposed. ## Claims ### Claim 1 A method programmed in a non-transitory memory of a device comprising: querying homomorphic encrypted information based on current acquired user information, wherein a query receives the current acquired user information as input, determines if a match is found in the homomorphic encrypted information without exposing the homomorphic encrypted information, and returns a result indicating the match being found or not; maintaining or increasing a user's trust score when the match is found in the homomorphic encrypted information; and decreasing a user's trust score when the match is not found in the homomorphic encrypted information. ### Claim 2 (depends on 1) The method of claim 1 further comprising: acquiring user information; and encrypting the user information using homomorphic encryption to be stored as the homomorphic encrypted information. ### Claim 3 (depends on 2) The method of claim 2 wherein the user information includes behavior and/or biometric information. ### Claim 4 (depends on 2) The method of claim 2 further comprising storing the user information in a database by classification. ### Claim 5 (depends on 2) The method of claim 2 further comprising continuously updating the user information. ### Claim 6 (depends on 5) The method of claim 5 wherein machine learning is used in continuously updating the user information. ### Claim 7 (depends on 2) The method of claim 2 wherein the homomorphic encryption comprises full homomorphic encryption. ### Claim 8 (depends on 1) The method of claim 1 wherein querying includes applying a logic operation with the current acquired user information and the homomorphic encrypted information to determine if the match is found. ### Claim 9 (depends on 1) The method of claim 1 wherein querying occurs without decrypting the homomorphic encrypted information. ### Claim 10 (depends on 1) The method of claim 1 further comprising providing access to a service when the match is found. ### Claim 11 A device comprising: a non-transitory memory for storing an application, the application configured for: querying homomorphic encrypted information based on current acquired user information, wherein a query receives the current acquired user information as input, determines if a match is found in the homomorphic encrypted information without exposing the homomorphic encrypted information, and returns a result indicating the match being found or not; maintaining or increasing a user's trust score when the match is found in the homomorphic encrypted information; and decreasing a user's trust score when the match is not found in the homomorphic encrypted information; and a processor configured for processing the application. ### Claim 12 (depends on 11) The device of claim 11 wherein the application is further configured for: acquiring user information; and encrypting the user information using homomorphic encryption to be stored as the homomorphic encrypted information. ### Claim 13 (depends on 12) The device of claim 12 wherein the user information includes behavior and/or biometric information. ### Claim 14 (depends on 12) The device of claim 12 wherein the application is further configured for storing the user information in a database by classification. ### Claim 15 (depends on 12) The device of claim 12 wherein the application is further configured for continuously updating the user information. ### Claim 16 (depends on 15) The device of claim 15 wherein machine learning is used in continuously updating the user information. ### Claim 17 (depends on 12) The device of claim 12 wherein the homomorphic encryption comprises full homomorphic encryption. ### Claim 18 (depends on 11) The device of claim 11 wherein querying includes applying a logic operation with the current acquired user information and the homomorphic encrypted information to determine if the match is found. ### Claim 19 (depends on 11) The device of claim 11 wherein querying occurs without decrypting the homomorphic encrypted information. ### Claim 20 (depends on 11) The device of claim 11 wherein the application is further configured for providing access to a service when the match is found. ### Claim 21 A method programmed in a non-transitory memory of a device comprising: acquiring user information; and encrypting the user information using homomorphic encryption to be stored as homomorphic encrypted information, wherein a query receives the current acquired user information as input, determines if a match is found in the homomorphic encrypted information without exposing the homomorphic encrypted information, and returns a result indicating the match being found or not; querying the homomorphic encrypted information based on current acquired user information; maintaining or increasing a user's trust score when the match is found in the homomorphic encrypted information; and decreasing a user's trust score when the match is not found in the homomorphic encrypted information. ### Claim 22 (depends on 21) The method of claim 21 wherein the user information includes behavior and/or biometric information. ### Claim 23 (depends on 21) The method of claim 21 further comprising storing the user information in a database by classification. ### Claim 24 (depends on 21) The method of claim 21 further comprising continuously updating the user information. ### Claim 25 (depends on 24) The method of claim 24 wherein machine learning is used in continuously updating the user information. ### Claim 26 (depends on 21) The method of claim 21 wherein the homomorphic encryption comprises full homomorphic encryption. ### Claim 27 (depends on 21) The method of claim 21 wherein querying includes applying a logic operation with the current acquired user information and the homomorphic encrypted information to determine if the match is found. ### Claim 28 (depends on 21) The method of claim 21 wherein querying occurs without decrypting the homomorphic encrypted information. ### Claim 29 (depends on 21) The method of claim 21 further comprising providing access to a service when the match is found.