Researchers Submit Patent Application, “Secure Identification Methods And Systems”, for Approval (USPTO 20230328417): Patent Application
2023 OCT 30 (NewsRx) -- By a
No assignee for this patent application has been made.
News editors obtained the following quote from the background information supplied by the inventors: “The
“The present disclosure pertains to novel solutions for trusted personal identification systems. In particular, to a system for the generation of unforgeable biometric physiology identification credentials and use of these unforgeable identification credentials for safe and secure transfer of services. Unforgeable identity may be ephemeral or persistent. Unforgeable identity may be local or distributed. Unforgeable identity may be closed/private or open/public. Unforgeable identity may be online or offline. Unforgeable identity may be at an individual (atom) or crowd/population (ecology) level.
“Biometric systems operate on behavioral and physiological biometric data to identify a person. Common behavioral biometric parameters are signature, gait, speech and keystroke, these parameters change with age and environment. Additional physiological characteristics such as face, fingerprint, palm print and iris largely remain unchanged throughout the life time of a person. The biometric system operates as verification mode or identification mode depending on the requirement of an application. The verification mode validates a person’s identity by comparing captured biometric data with ready-made template. The identification mode recognizes a person’s identity by performing matches against multiple fingerprint biometric templates. Fingerprints are widely used in daily life for more than 100 years due to its feasibility, distinctiveness, permanence, accuracy, reliability, and acceptability.
“Separately, over the past decade, there has been significant innovation in distributed ledger technologies (DLTs). Blockchain technology, a form of DLT, allows a network of independent peer nodes to maintain a consistent view of shared state through consensus, thus enabling decentralized trust. This technology is the basis for well-known decentralized permissionless networks such as Bitcoin [
“Additionally, over the past several years Decentralized Identity (DID) technology has also seen significant innovation and standardization. With over fifty organizations participating in the W3C Decentralized Identifier working group; including Microsoft, Intel,
As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “Aspects of the present disclosure contemplate end to end unforgeable Uniform Biometric Identifier and Uniform Biometric Locator systems, which are implemented separately and are interoperable with existing distributed ledger technologies. This implemented technology can; 1) generate a “verifiable credential”, 2) prove “access control” attributes related to said “verifiable credential”, 3) deliver “conditional access” capability by extending “verifiable credential”, and “access control” primitives with “state and status biometrics” through its sensor fusion technology.
“In certain aspects, there is provided a Decentralized Identifier technology, referred to herein as uDIDt.
“In certain aspects, there is provided methods and systems for generating a unique verifiable credential identifier of a person, referred to herein as uDIDt-VeCx.
“In certain aspects, there is provided methods and systems for using the uDIDt-VeCx for proof of “access control” based on “verifiable credential” attributes in secure transactions. Transactions may include any type of transaction such as a commercial transaction, a security clearance, machinery or autonomous vehicle, and the like.
“In certain embodiments, methods and systems of the present technology may be used for “access control”/“conditional access” by extending “verifiable credentials” for health/travel passports during pandemic or disaster emergencies.
“In certain embodiments, methods and systems of the present technology may be used for current health state and status confirmation at ports-of-entry.
“In certain embodiments, methods and systems of the present technology may be used for generating a “verifiable credential” or “keycard” for entry.
“In certain embodiments, the novel biosignature unforgeable globally unique identifier (uDIDt-VeCx) is based on an integration of central nervous system and autonomic nervous system biofield signatures that are immutable and valid only during the time that a person is alive (also referred to herein as “biosignature”). The biosignature may include data relating to any physiological parameter of the person (see Table 1 for examples).
“All current attempts at unique identifiers relieve the individual of any control on how they are identified. Current unique identifiers are issued by external authorities that decide who or what they identify and when they can be revoked. They are useful only in certain contexts and recognized only by certain bodies (not of the individual’s choosing). They may disappear or cease to be valid with the failure of an organization. They may unnecessarily reveal personal information. And in many cases, they can be fraudulently replicated and asserted by a malicious third-party (“identity theft”).
“The unique Decentralized Identifier technology (uDIDt) defined in this disclosure is a new type of globally unique identifier designed to enable individuals and organizations to generate their own identifiers (uDIDt-VeCx) using systems they trust, and to prove control of those identifiers (authenticate) using cryptographic proofs (eg., digital signatures, privacy-preserving biometric protocols, etc).
“The current technology may comprise embodiments disclosed in the patent application
“In the context of the present specification, unless expressly provided otherwise, a computer system may refer, but is not limited to, an “electronic device”, an “operation system”, a “system”, a “computer-based system”, a “controller unit”, a “control device” and/or any combination thereof appropriate to the relevant task at hand.
“In the context of the present specification, unless expressly provided otherwise, the expression “computer-readable medium” and “memory” are intended to include media of any nature and kind whatsoever, non-limiting examples of which include RAM, ROM, disks (CD-ROMs, DVDs, floppy disks, hard disk drives, etc.), USB keys, flash memory cards, solid state-drives, and tape drives.
“In the context of the present specification, a “database” is any structured collection of data, irrespective of its particular structure, the database management software, or the computer hardware on which the data is stored, implemented or otherwise rendered available for use. A database may reside on the same hardware as the process that stores or makes use of the information stored in the database or it may reside on separate hardware, such as a dedicated server or plurality of servers.
“In the context of the present specification, unless expressly provided otherwise, the words “first”, “second”, “third”, etc. have been used as adjectives only for the purpose of allowing for distinction between the nouns that they modify from one another, and not for the purpose of describing any particular relationship between those nouns.
“Embodiments of the present technology each have at least one of the above-mentioned object and/or aspects, but do not necessarily have all of them. It should be understood that some aspects of the present technology that have resulted from attempting to attain the above-mentioned object may not satisfy this object and/or may satisfy other objects not specifically recited herein.
“Additional and/or alternative features, aspects and advantages of embodiments of the present technology will become apparent from the following description, the accompanying drawings and the appended claims.
“It should be noted that, unless otherwise explicitly specified herein, the drawings are not to scale.”
The claims supplied by the inventors are:
“1. A method for generating a unique identifier for a subject, the method executable by a processor of a computer system, the method comprising: obtaining biometric data relating to the subject; extracting identification markers from the biometric data; generating the unique identifier from the extracted identification markers, wherein the generating the unique identifier comprises identifying a given domain specific feature which has predetermined identity compared to other domain specific features.
“2. The method of claim 1, wherein the predetermined identity has a higher occurrence than other domain specific features.
“3. The method of claim 1, wherein the predetermined identity comprises a higher frequency event than other domain specific features.
“4. The method of claim 1, wherein the domain comprises one or more of acoustic signals, vibroacoustic signals, electromagnetic signals and optical signals.
“5. The method of claim 1, wherein the given domain specific feature is characterized based on one or more of a pitch, an amplitude, a peak, an area under the curve, a frequency, a spectral distribution, a total energy, a timbre, a timing, frequency bands, and harmonic distribution.
“6. The method of claim 1, further comprising storing the generated unique identifier in a database of the processor.
“7. The method of claim 1, wherein the generating the unique identifier occurs at a first time point, the method further comprising, at a second time point, comparing the generated identifier with a reference identifier to determine a presence of predetermined common features.
“8. The method of claim 7, wherein the second time point is later than or at the same time as the first time point.
“9. The method of claim 1, further comprising one or more of: determining whether to accept the biometric data based on predetermined criteria; processing the biometric data to enhance a signal thereof; processing the biometric data to normalize a signal thereof; processing the biometric data to perform evolutionary structural machine learning, signal aggregation and abstraction of a signal thereof; and comparing the biometric data to reference biometric data stored in a database.
“10. The method of claim 1, wherein the generated unique identifier is a QR code.
“11. The method of claim 1, wherein the obtaining the biometric data comprises a baseline phase and a base-line update phase, a data segment in the baseline phase being larger than a data segment in the base-line update phase.
“12. The method of claim 1, wherein the obtaining the biometric data comprises acquiring data at sampling rates of about 0.01 Hz to about 20 THz.
“13. The method of claim 1, further comprising causing the processor to send the generated unique identifier to a given device, such as by Bluetooth.
“14. The method of claim 1, further comprising adding a time stamp to the generated unique identifier.
“15. The method of claim 1, further comprising obtaining input of an event related parameter, such as attending a given show, banking with a given bank, becoming infected with a given virus, and generating a status identifier incorporating information about the unique identifier and the event.
“16. The method of claim 1, further comprising obtaining input of a physical identification parameter from a device associated with the subject.
“17. The method of claim 1, further comprising converting a bit output of the generated unique identifier according to a bit requirement of another digital identification solution which has a different requirement.
“18. The method of claim 1, further comprising obtaining input of an emotional/cognitive state of the subject, and incorporating with the generated unique identifier.
“19. The method of claim 1, further comprising use of the generated unique identifier as one or more of a health passport; security access; emotional/cognitive feedback.
“20. A system for generating a unique identifier for a subject, the system comprising a processor of a computer system, the processor configured to execute a method as described in any one of claims 1-19.
“21. The system of claim 20, further comprising one or more sensors for obtaining the biometric data.
“22. The system of claim 20, wherein the computer system is at least partially implemented in a mobile device, the mobile device further including a physical identification portion.
“23. A method comprising: receiving an identifier of an individual; retrieving a profile corresponding to the individual from a database of user profiles; recording biometric data of the individual using a sensor array, wherein the sensor array comprises a vibroacoustic sensor; retrieving an ordered list of features; generating, based on the biometric data, one or more feature values corresponding to highest-ranked features in the ordered list of features; determining a user profile from the database of user profiles that matches the one or more feature values; after determining that the user profile from the database matches the retrieved profile corresponding to the individual, outputting an indication that the individual has been authenticated.
“24. The method of claim 23, wherein receiving the identifier of the individual comprises scanning a bar code corresponding to the individual.
“25. The method of claim 23, wherein receiving the identifier of the individual comprises receiving a username of the individual.
“26. The method of claim 23, wherein receiving the identifier of the individual comprises receiving an identification number corresponding to the individual.
“27. The method of claim 23, wherein the profile corresponding to the individual comprises a plurality of feature values, and wherein the feature values are based on previously recorded measurements of the individual.
“28. The method of claim 23, wherein the ordered list of features was generated by a machine learning algorithm (MLA) trained to rank features based on their ability to discriminate between individuals.
“29. The method of claim 28, wherein features that are more likely to discriminate between individuals are assigned a higher ranking in the ordered list of features.
“30. The method of claim 23, wherein determining the user profile that matches the one or more feature values comprises iterating through the ranked list of features until a unique profile matching the biometric data of the individual is found.
“31. The method of claim 23, wherein determining the user profile that matches the one or more feature values comprises iterating through the ranked list of features until an amount of potential matches for the biometric data of the individual is less than a predetermined threshold amount.
“32. The method of claim 23, wherein the sensor array comprises one or more environmental sensors, wherein the method further comprises measuring, by the one or more environmental sensors, one or more environmental parameters, and wherein generating the one or more feature values comprises generating the one or more feature values based on the one or more environmental parameters.
“33. A method comprising: recording biometric data of an individual using a sensor array, wherein the sensor array comprises a vibroacoustic sensor; generating, based on the biometric data, a plurality of feature values; generating a user profile of the individual, wherein the user profile comprises the plurality of feature values; storing the user profile in a database; generating, by a machine learning algorithm (MLA) and based on the database, a ranked list of features wherein the features are ranked based on their likelihood to discriminate between individuals; and storing the ranked list.
“34. The method of claim 33, further comprising: recording, by the sensor array, one or more environmental parameters; and storing the one or more environmental parameters in the user profile.
“35. The method of claim 34, wherein the one or more environmental parameters comprise a measured temperature and a measured humidity.
“36. The method of claim 33, wherein the database comprises a graph.
“37. A system comprising: at least one processor, and memory storing a plurality of executable instructions which, when executed by the at least one processor, cause the system to execute a method as described in any one of claims 23-36.”
For additional information on this patent application, see: HAMMOND, Kevin; JUMBE, Nelson L.; KRAWIEC, Krzysztof; MORIMOTO, Michael; ROOKE, Todd; SCHUH, Andreas. Secure Identification Methods And Systems.
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