AU2020100425A4 - SafeEShare - Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own. - Google Patents

SafeEShare - Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own. Download PDF

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AU2020100425A4
AU2020100425A4 AU2020100425A AU2020100425A AU2020100425A4 AU 2020100425 A4 AU2020100425 A4 AU 2020100425A4 AU 2020100425 A AU2020100425 A AU 2020100425A AU 2020100425 A AU2020100425 A AU 2020100425A AU 2020100425 A4 AU2020100425 A4 AU 2020100425A4
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data
user
identifier
sharing
communication
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AU2020100425A6 (en
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Julianne Mary Cripps Clark
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Abernethy Healthy Lifestyle Ass Inc
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures
    • G06F21/645—Protecting data integrity, e.g. using checksums, certificates or signatures using a third party
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/08—Key distribution or management, e.g. generation, sharing or updating, of cryptographic keys or passwords
    • H04L9/0816—Key establishment, i.e. cryptographic processes or cryptographic protocols whereby a shared secret becomes available to two or more parties, for subsequent use
    • H04L9/0838—Key agreement, i.e. key establishment technique in which a shared key is derived by parties as a function of information contributed by, or associated with, each of these
    • H04L9/0847—Key agreement, i.e. key establishment technique in which a shared key is derived by parties as a function of information contributed by, or associated with, each of these involving identity based encryption [IBE] schemes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3236—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using cryptographic hash functions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • G06F21/6254—Protecting personal data, e.g. for financial or medical purposes by anonymising data, e.g. decorrelating personal data from the owner's identification

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  • Engineering & Computer Science (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Theoretical Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Bioethics (AREA)
  • Computer Hardware Design (AREA)
  • Software Systems (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Epidemiology (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

SafeEShare Patents Act 1990 INNOVATION PATENT Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own. Onus of recognition remains with the data producer but functionality classifying, controlling and identifying data elements via hierarchies rests with the party most benefitting from its control including device level switching. Sharing restrictions are implemented via blockchain. Re-combination of different items of depersonalized data requires the cooperation of the person producing the original data. Re-sharing by DataAgencies of depersonalized data is assumed to be an allowable commercial imperative managed external to the system. The data model on the DataAgency side includes structures for measurement quality management, hierarchical classifications and boundary control.

Description

DESCRIPTION
INNOVATION PATENT
Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own. Onus of recognition remains with the data producer but functionality classifying, controlling and identifying data elements via hierarchies rests with the party most benefitting from its control including device level switching. Sharing restrictions are implemented via blockchain. Re-combination of different items of depersonalized data requires the cooperation of the person producing the original data. Re-sharing by DataAgents of depersonalized data is assumed to be an allowable commercial imperative managed external to the system. The data model on the DataAgent side includes structures for measurement quality management, hierarchical classifications and boundary control.
Data producers maintain a PERSONAL permission profile classifying hierarchy for data sources on personal devices connected to sensor devices. This expandable hierarchy (eg device source, type, time of day, storage location,...) is able to recognize a variety of proforma legal service contract relationships including agency first ownership of specified streams of depersonalized data .
Once the data stream and the DataAgent have both been configured during operation according to that hierarchy each shareable data item is tagged with : a MappedSharing Identifier (being a foreign key that indicates the extent and nature of sharing allowed by the data owner for that data item by virtue of its match to the owner's classification system) and the DataAgent Identifier for the DataAgent that will own the first depersonalized copy of it. It is envisaged that restrictions on storage location would be enforced by reference to the originating data source only for the first DataAgent. Regulatory approaches to retransfers by DataAgents will be relied on to sufficiently ensure accountability for sharing of depersonalized data that encourages preservation of strongest possible evidence bases.
The default DataAgency is 0. The meaning of 0 is determined by a global ShareData setting for the device at configuration settings level ie NONE or SHARE. SHARE means the depersonalized data co-owned by DataAgent 0 is available for everyone. NONE means the depersonalized data co-owned by DataAgent = 0 is not shared with anyone. It will not be messaged out. Specific sharing with a DataAgent requires a DataAgent identifier that will identify messages containing the dataset at the DataAgents end.
Sharing of the depersonalized data record is accomplished by pre-pending the element of the data stream being shared with the DataAgent Identifier and a MappedSharing Identifier (being a foreign key related to the data stream record for the data stream that this owner is prepared to share as well as a particular DataAgentPermit (eg sharing details for a particular agent or researcher in a particular medical intervention) in which the owner has consented to participate, optionally with start and end sharing dates & times.
An identified data stream can be shared with more than one DataAgent by the owner. So long as each receiving DataAgent does not destroy the original pre-pended MappedSharing Identifier, duplication of data will be detectable. So long as the data producer maintains their history of sharing episodes, they will be able to, and will actually need to facilitate re-assembly of different items of shared data through blockchain request messages issued by DataAgent, including where that DataAgent was not the original first agent.
The data stream part of the message sent out over the internet contains a record meaningful to the DataAgent collecting it. For example a measurement record of mspeclD=234 might have been defined to be a heartbeat measurement measured in a certain way. The way it is measured would be configured as a ProcedureForMeasurement. The structure (or meta-data) of measurement records as supported by the description field in the mspec record would indicate to
SafeEshare
2020100425 19 Mar 2020 everyone at that DataAgency that the fifth part of the measurement record is a number representing beats per minute, the sixth part of the record is a date and time value and the second part of the record is an identifier that gives information about how that measurement was captured in the first place.
Sharing of the record once communicated online is controlled through blockchain principles such that the sharing system verity can be managed and audited through relevant industry and national regulatory systems.
Further data infrastructure at the DataAgent end is required for DataAgents working in the health field for research purposes. Each research institute maintains a list of its subscribers (ie people who are providing data to them) and depersonalise this data as a matter of principle. The subscriber identifier at that institution for that experiment/intervention would be used to produce the DataAgent ID provided by that institute to the user at data stream setup time. As most of these subscriptions are for the purpose of a particular experiment or intervention, the scheme includes infrastructure implementing qualification. The DataAgent is able to check that the intervention participant/subscriber remains within the bounds of eligibility for that particular measurement and therefore configure the data for this particular intervention (or if there is more than one class of participant by virtue of different ranges for that particular measure) to be 'automatically' classified into the correct grouping. It may be that this intervention is only testing people whose rest pulse is between 60bpm and 80bpm and who have brown eyes.
In this scheme a measurement would also be able to be used to store static data - as a different mspec (eg for eye colour a limited set of values as detailed in the mspec description could be used) for collection in another part of the same intervention program using a different ProcedureForMeasurement. Think of it as a survey delivered as per the schedule datetime field in the relevant ScheduledProcedure for this particular Intervention and with questions determined by the ProcedureForMeasure procID which is indicated in the ScheduledProcedure record. (NB There are extra tables and fields not shown in the demo schema that would be required for a 'survey question' mspeclD. Without them this particular schema cannot work as a survey with component questions properly. To avoid further complexity in this explanation though these details have been left out. Let's just say for now that here if the measurement being used to classify a measurement record is a type 564 record, then the third part of the record is instead a pointer to a questionnaire record, whereas in all other respects a type 564 measurement record is similar in structure to the type 234 measurement record.)
Using even just the cutdown schema discussed here, the set of all participants who fit these combined criteria (the set of InterventionSubsetCharacterisation nodes) at the time the criteria is 'open' can be tracked and scheduled for other procedures dynamically without identification of the individuals. This allows data from these individuals to be applied as existing sample data (with an existing and potentially already sufficient history of measurements) for newer designed interventions in a reasonably efficient way but still anonymous way, only limited by the necessary permission protocols.
To do it, researchers would filter InterventionSubsetCharacterisation using the first part (ie the primary key) from the intervention record that detailed an experiment that sounded like it might have matching qualification data and which dictated that this data be collected (It might be being stored by a health department data registration centre somewhere as a function of the nationally defined process for setting up a registered measured intervention). All applicable measurements would be accessible via the InterventionMeasureList (yet another record, owned by the research institute that designed the original intervention) listing the originating intervention measurement's intervention key along with a field containing the measurement type of 234 and a third field containing an InterventionSubsetCharacterisation identifier (keyed into a multidimensional matrix of selection criteria (eg males, age 25-60, living in SA3-Lower Hunter, characteristicA on startdate, characteristicB on startdate, characteristicC when collected, characteristic D when collected etc) which the new researcher may even refine without compromising the original structure (InterventionSubsetBoundaries are hierarchically arranged. The higher resolution MSpec would be added again as a child InterventionSubsetBoundaries record.). It is via this mechanism that researchers and statisticians could access already collected data and assess it as being statistically powerful for other interventions - so long as the list
SafeEshare
2020100425 19 Mar 2020 of categorisations of the intervention subset lists was well planned and maintained, and changes to it were continually reflected properly only as new records (ie attached hierarchically to less refined sets if need be).
This categorisation (InterventionSubsetBoundaries) list would contain records containing a measurement type, a range description and a pointer back into the list identifying its superset. Each categorisation would include at least four fields eg a record for smoking history categorisation might include:- • the category key (ie the primary id called iscID, used for referral to this group in sub groups and in other records), • Access to the categorisation description smoking history via mspecID, • a range Gave Up for longer than a year on a known date (or an upper and lower boundary) and • a pointer to its parent categorisation Smoked at least once.
A second record related to smoking might the next category identified as four fields containing firstly the primary category key, secondly the description smoking history, thirdly the range Gave up at least once on an unknown date and finally a pointer to its parent category Smoked at least once.
This categorisation process and its hierarchy is complex and so the structure supporting it is also likely to be. The easiest way to think of it is to think of a Christmas tree with a piece of string attached to every branch at one end and threaded through its very own hole in a colander at the other end above the Christmas tree. Every time a new branch grows, it is strung into a spare colander hole which is named in some meaningful way so it can be found again by statisticians (but not necessarily with any reference to the originating research that put it there because it may be used for data by more than one intervention).
The measurement record does not need to be stored with any identifying data and yet it can be assessed and possibly included in testing for other interventions along with all the other measured information that was stored for that individual at the same time based on its relationship to an InterventionSubsetBoundaries record. Analysis of other measurements taken under other subscriptions can also be used to rule that data eligible for inclusion in alternative interventions. Subject to signup protocols the analyst can use the Subscription record (links to a common person without identifying the individual) to access depersonalised data about this individual even if the intervention is not the same one for which the measurement was designed and collected in the first place.

Claims (5)

  1. INNOVATION PATENT
    1. A Method comprising :
    Receiving by a device and from a user device or directly downloading and configuring at the device itself an app for sharing data between devices;
    Receiving by a device and from a user device a communication defining measurement records or other pieces of data from the user device as a data stream of potentially shareable data;
    Receiving by a device from a user device or a communication or directly inputing at the device itself an identifier relating to a specific DataAgent hoping to accept communications containing specified items of data from the device;
    Identifying a mapped data stream with source device details for sharing depersonalized data by communication to other devices;
    Receiving by a device from a user device or directly configuring at the device itself permission profile information arranged as a taxonomy of identified permission profiles built for the purpose of determining and packing data stream elements into messages, and from which taxonomy, shareable data can be explicitly classified as belonging to a classification pertaining to all configured possibilities which are explicitly mapped to both :
    a categorization of any device producing data into the mapped stream, and a categorization of the nature of any item of data issuing from the mapped stream;
    Receiving by a device from a user device or directly configuring at the device itself an identifier relating to a specific DataAgentPermit as a pairing of a DataAgent identifier with a PermissionProfile identifier;
    Receiving by a device from a user device or directly configuring at the device itself an identifier relating to a mapped sharing of identified data via the pairing of a DataAgentPermit with a user's depersonalized data stream;
    Receiving by a device from a user device or directly configuring at the device itself private intervention subscription data from the user as a secure separate communication;
    Packaging and communicating data received by a device from a user device as a mapped sharing of measurement records or other pieces of data and tagged with the DataAgent identifier and a MappedSharing identifier.
  2. 2. The method of claim 1, wherein performing the one or more actions includes one or more of:
    Receiving by a device from a user device or a communication or directly inputing at the device itself information relating to measurement procedures;
    Processing of the information about the data stream to include optional start and end dates;
    Processing the measurement procedure as required by calibration length;
    Processing of the information about the data stream to include information related to the measurement procedure;
    Processing of the information about the data stream to include periodic filtering information;
    2020100425 19 Mar 2020
    SafeEShare
    Processing the taxonomy of identified Permissionprofiles that determines data release and message packing to include extra classifications such that data streams are processed according to each of any extra existing configured permission classifications which can be any or all of:
    an account producing the data, the defined date and/or time of day period the data is shareable from the device, the periodicity of the data to be sent off, the measurement procedure used, the calibration cycle length, the jurisdiction in which the producing user or account holder accepts to share the data;
    Processing the DataAgentPermit by switching it on or off;
    Receiving a message containing a DataAgency identifier that removes or switches off all sharing profiles matching that DataAgent identifier;
    Checking the permission profile identifier still exists;
    Checking calibration time stamps against the calibration cycle length;
    Packaging mapped sharing records with foreign keys and a datetime stamp related to the measurement procedure.
    Receiving by a device and from a user device an app for recording requests to link depersonalized data back together by listing;
    Confirming a users ownership of any stored MappedSharing identifier matching the particular DataAgent identifier it was created for and assigning the same random depersonalized grouping identifier to all such confirmed MappedSharing identifier seeking messages that the user is prepared to allow to be linked together and communicating the link mapping to the requesting DataAgent;
  3. 3. The method of claim 1, further comprising:
    Implementing an hierarchy of orthogonal dimensions that together constitute a taxonomical scheme for characterisations being tested against particular physical qualities being measured within an intervention that is managed by the Datallser, and including at each characterization layer in the taxonomical scheme, a categorization of 'unknown' for that characterisation;
    Accepting intervention subscriptions by linking their MappedSharing Identifier to biographical and other kinds of private data collected directly from the user;
    Using depersonlised information collected about a user to augment and then classify data collected from users as streams for insertion in the hierarchy;
    Implementing and maintaining an extension hierarchy at each node defining the value of upper and lower boundaries hierarchically mapped for each categorization pertinent to the analysis of the intervention;
    Creating a single description record at each node in the extension part of the hierarchy that includes data names and value ranges for each consecutive layer of the whole hierarchy and use these hierarchically to match and then check boundaries of incoming shared depersonalized data;
    Assign each incoming item of depersonalized data its correct leaf node identifier;
    Reassign data to end nodes when additional boundaried classes of data are created;
    2020100425 19 Mar 2020
    SafeEShare
    Assign data from other interventions.
  4. 4. A Device comprising:
    one or more memories; and one or more processors, communicatively coupled to the one or more memories, to:
    receive, from a user device, a communication associated with a support issue encountered by a user of the user device;
    receive, from a user device, a communication associated with data produced by a user of the user device; receive information identifying one or more self-support actions performed by the user in relation to the support issue;
    receive information identifying one or more self-support actions performed by the user in relation to the data being shared;
    assign the communication to a position in a support queue based on when the communication is received, wherein the support queue includes:
    information identifying positions of other communications received from other users, information identifying when the other communications are received, and information identifying self-support actions performed by the other users;
    associate the information identifying the one or more self-support actions performed by the user with information identifying the position of the communication in the support queue;
    apply respective weights to the one or more self-support actions performed by the user;
    generate a score for the communication based on applying the respective weights to the one or more selfsupport actions performed by the user;
    modify the position of the communication in the support queue based on the score; and perform one or more actions based on modifying the position of the communication in the support queue.
  5. 5. A Device or Graphical Representation comprising : various things yet to be fully claimed.
AU2020100425A 2020-03-19 2020-03-19 SafeEShare - Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own. Active AU2020100425A6 (en)

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AU2020100425A AU2020100425A6 (en) 2020-03-19 2020-03-19 SafeEShare - Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own.

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AU2020100425A AU2020100425A6 (en) 2020-03-19 2020-03-19 SafeEShare - Devices assemble data records, from private and/or possibly sensitive sources, of type or types that may be useful for sharing in varying degrees with other interests that the owner hopefully recognizes operate with interests different and possibly even in conflict with his/her own.

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115361298A (en) * 2022-07-16 2022-11-18 中国航空工业集团公司洛阳电光设备研究所 Service management method based on data subscription and distribution network

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115361298A (en) * 2022-07-16 2022-11-18 中国航空工业集团公司洛阳电光设备研究所 Service management method based on data subscription and distribution network
CN115361298B (en) * 2022-07-16 2023-06-20 中国航空工业集团公司洛阳电光设备研究所 Service management method based on data subscription distribution network

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Legal Events

Date Code Title Description
FGI Letters patent sealed or granted (innovation patent)
PC Assignment registered

Owner name: CRIPPS CLARK, JULIANNE

Free format text: FORMER OWNER(S): CRIPPS CLARK, JULIANNE; ABERNETHY HEALTHY LIFESTYLE ASSOCIATION INCORPORATED

DA3 Amendments made section 104

Free format text: THE NATURE OF THE AMENDMENT IS AS SHOWN IN THE STATEMENTS FILED 13 APR 2021, 22 APR 2021 AND 24 MAY 2021