WO2023228560A1 - データ集計装置 - Google Patents

データ集計装置 Download PDF

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Publication number
WO2023228560A1
WO2023228560A1 PCT/JP2023/012842 JP2023012842W WO2023228560A1 WO 2023228560 A1 WO2023228560 A1 WO 2023228560A1 JP 2023012842 W JP2023012842 W JP 2023012842W WO 2023228560 A1 WO2023228560 A1 WO 2023228560A1
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WIPO (PCT)
Prior art keywords
data
aggregation
unit
group
calculation
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PCT/JP2023/012842
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English (en)
French (fr)
Japanese (ja)
Inventor
佳純 斧田
雅之 寺田
博 青野
智尋 中川
慶太 長谷川
一真 野澤
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NTT Docomo Inc
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NTT Docomo Inc
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Priority to US18/867,292 priority Critical patent/US20250328689A1/en
Priority to JP2024522945A priority patent/JPWO2023228560A1/ja
Publication of WO2023228560A1 publication Critical patent/WO2023228560A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries

Definitions

  • One aspect of the present disclosure relates to a data aggregation device that collates and aggregates data held by two or more organizations.
  • Patent Document 1 listed below discloses a job processing system in which a matching batch process for matching first data and second data, each of which has a plurality of items, is distributed to a plurality of calculation servers and processed. .
  • a data aggregation device is a data aggregation device that collates and aggregates data that is held by two or more organizations and that is associated with individuals and groups, and that collates and aggregates data that is associated with individuals and groups.
  • the apparatus includes a totaling unit that compares and totals data associated with a matching identifier, which is an identifiable identifier, for each group based on the matching identifier.
  • data is compared and aggregated for each group based on the matching identifier.
  • data can be matched for each group.
  • data can be matched for each group.
  • FIG. 1 is a diagram illustrating an example of a system configuration of a data aggregation system including a data aggregation device according to an embodiment. It is a diagram showing data linkage of data held by two companies.
  • FIG. 1 is a diagram illustrating an example of a functional configuration of a data aggregation device according to an embodiment. It is a diagram showing an example of data held by Company A. 5 is a diagram showing an example of data in which a matching identifier is associated with the data shown in FIG. 4.
  • FIG. FIG. 1 is a diagram illustrating an example of a functional configuration of a data transmitting device according to an embodiment. It is a diagram showing an example of data held by company B.
  • FIG. 8 is a diagram showing an example of data in which a matching identifier is associated with the data shown in FIG. 7;
  • FIG. 9 is a diagram showing a scene in which the data shown in FIG. 5 and the data shown in FIG. 8 are compared and totaled.
  • FIG. FIG. 3 is a diagram showing an example of aggregated data for each group.
  • FIG. 3 is a diagram illustrating an example of aggregated data obtained by integrating aggregated data for each group.
  • FIG. 3 is a diagram illustrating an example of statistical information in which noise is added to integrated aggregated data.
  • FIG. 2 is a sequence diagram illustrating an example of processing executed by the data aggregation system.
  • FIG. 3 is a diagram illustrating another example of processing executed by the data aggregation system.
  • FIG. 3 is a diagram illustrating an example in which usefulness decreases due to the influence of noise.
  • FIG. 3 is a diagram illustrating a problem when aggregation is performed separately for each group.
  • FIG. 2 is a diagram illustrating a problem when generating a matching identifier and merging data of a plurality of groups.
  • 1 is a diagram illustrating an example of a hardware configuration of a computer used in a data aggregation device according to an embodiment.
  • FIG. 1 is a diagram showing an example of a system configuration of a data aggregation system 3 including a data aggregation device 1 according to an embodiment.
  • the data aggregation system 3 includes a data aggregation device 1 and a data transmission device 2.
  • the data aggregation device 1 and the data transmission device 2 are communicatively connected to each other via a network such as the Internet, and are capable of transmitting and receiving information to and from each other.
  • a network such as the Internet
  • the present embodiment will be described assuming that there is one data transmitting device 2, the present invention is not limited to this, and there may be a plurality of data transmitting devices.
  • each data transmitting device 2 is communicatively connected to the data aggregation device 1 via a network, and can send and receive information to and from each other.
  • the data aggregation device 1 is a computer (server) device that collates and aggregates data held by two or more organizations and associated with individuals and groups.
  • this embodiment will be described assuming two organizations, Company A and Company B, but the present invention is not limited to this and may be three or more organizations.
  • the data aggregation device 1 is managed by company A and stores data held by company A. It is also assumed that the data is associated with individuals and groups.
  • the data transmitting device 2 is managed by company B and stores data owned by company B. Similarly, it is assumed that the data is associated with individuals and groups.
  • the data aggregation device 1 compares and totals the data held by company A stored in the data aggregation device 1 and the data held by company B stored in the data transmission device 2.
  • FIG. 2 is a diagram showing the data linkage of data held by each of the two companies. Specifically, FIG. 2 shows data linkage (matching, aggregation, etc.) between data held by company A, which is stored in the data aggregation device 1, and data held by company B, which is stored in the data transmission device 2. It is shown that. Note that in data linkage, data may be linked without revealing each other's data. In that case, no one knows the data that is being compared and aggregated. Examples of methods for linking data without revealing each other's data include non-identification processing, secret calculation, and concealment processing. Details will be described later.
  • a group is a group of people or things classified based on common characteristics. The groups are, for example, by day of the week, by event, by flight, or by purchased item.
  • a group may be a unit of aggregation when comparing data.
  • a group may be a unit of aggregation when two or more companies compare data based on a user identifier that identifies an individual. For example, when comparing data divided by day of the week, the aggregation unit for this comparison is a group.
  • the data that is associated with the same group there may be no duplication of individuals that are associated with the same group. That is, there may be no duplication of user identifiers within the group.
  • a configuration may also be adopted in which there is always no duplication of user identifiers within a group.
  • the name "user" corresponding to an individual is not a user of the data aggregation device 1, but a general, broad meaning. Refers to users of
  • the data transmission device 2 is a computer (server) device that stores data owned by Company B.
  • the data transmission device 2 transmits data to be stored or data based on the data to the data aggregation device 1 for comparison and aggregation in the data aggregation device 1.
  • FIG. 3 is a diagram showing an example of the functional configuration of the data aggregation device 1 according to the embodiment.
  • the data aggregation device 1 includes a storage section 10, an input section 11, an aggregation section 12 (aggregation section), an arithmetic section 13 (arithmetic section), a secret section 14 (a secret section), and an output section 15. configured.
  • each functional block of the data aggregation device 1 is assumed to function within the data aggregation device 1, it is not limited to this.
  • some of the functional blocks of the data aggregation device 1 are computer devices different from the data aggregation device 1, and are capable of transmitting and receiving information to and from the data aggregation device 1 as appropriate within a computer device connected to the data aggregation device 1 through a network. It is possible to function while doing so.
  • some functional blocks of the data aggregation device 1 may be omitted, multiple functional blocks may be integrated into one functional block, or one functional block may be decomposed into multiple functional blocks. good.
  • the storage unit 10 stores arbitrary information used in calculations in the data aggregation device 1, results of calculations in the data aggregation device 1, and the like.
  • the storage unit 10 stores data owned by the above-mentioned company A.
  • the information stored by the storage unit 10 may be appropriately referenced by each function of the data aggregation device 1.
  • the input unit 11 inputs data to be matched (for comparison between the two).
  • the data to be entered is associated with individuals and groups.
  • the input unit 11 inputs data stored by the storage unit 10 and owned by Company A.
  • the input unit 11 may input data divided into groups.
  • FIG. 4 is a diagram showing an example of data held by Company A.
  • the data shown in FIG. 4 is a user list that is a list of individuals for each group.
  • the user list includes individuals such as group 1 "Monday” whose group identifier identifying the group is “Monday” and user identifiers identifying individuals such as "aaa” and "bbb".
  • Group 2 "Tuesday” whose group identifier is "Tuesday” includes individuals whose user identifiers for identifying individuals are "aaa” and "bbb.” That is, the user list is associated with individuals and groups.
  • the data included in the group in the user list is only the user identifier, but the data is not limited to this, and a plurality of data may be included.
  • data regarding one or more attributes eg, gender and age
  • one or more attributes eg, gender and age
  • the input unit 11 generates and associates a matching identifier, which is an identifier that can identify individuals and groups of the data, with the input data.
  • the input unit 11 generates a matching identifier from a group identifier that identifies a group to be matched and a user identifier.
  • the matching identifier identifies a group of data to be matched.
  • FIG. 5 is a diagram showing an example of data in which matching identifiers are associated with the data (user list) shown in FIG. 4.
  • the input unit 11 generates a matching identifier "AAA$" from the user identifier "aaa” and the group identifier "Monday", for example, and associates it with the user list.
  • “AAA$” corresponds to the user identifier "aaa” (linked)
  • "$" corresponds to the group identifier "Monday” (linked).
  • the input unit 11 generates a matching identifier "BBB$" from the user identifier "bbb” and the group identifier "Monday”, and generates a matching identifier "AAA” from the user identifier "aaa” and the group identifier “Tuesday”.
  • a matching identifier "BBB#” is generated from the user identifier "bbb” and the group identifier "Tuesday” and is associated with the user list. Note that among the matching identifiers, "BBB” corresponds to the user identifier "bbb” (linked), and “#” corresponds to the group identifier "Tuesday” (linked).
  • the matching identifier is set as "AAA$" to make it easier to understand the correspondence between the user identifier "aaa” and the group identifier "Monday”, but the input unit 11 excludes the correspondence.
  • a matching identifier may be generated and then associated.
  • the input unit 11 may use data (irreversibly converted data) obtained by applying a hash function to data based on a combination of a user identifier and a group identifier as the matching identifier.
  • the user list associated with matching identifiers includes matching identifiers "AAA$” and “BBB$” in group 1 "Monday”, and matching identifiers "AAA$” and “BBB$” in group 2 "Tuesday”. Identifiers such as “AAA#” and "BBB#” may be included.
  • the input unit 11 may output the data associated with the matching identifier to the aggregation unit 12 or may cause the storage unit 10 to store the data.
  • the input unit 11 inputs calculation information regarding a predetermined (arbitrary) calculation (calculation method).
  • the predetermined calculation may be a calculation specified in advance by the user (of the data aggregation device 1), or may be a calculation indicated by calculation information stored in advance by the storage unit 10.
  • the predetermined calculation may be, for example, a total of all groups (or weekly total, etc.), an average, or a difference.
  • the input unit 11 may output the calculation information to the aggregation unit 12 or may cause the storage unit 10 to store the calculation information.
  • FIG. 6 is a diagram showing an example of the functional configuration of the data transmitting device 2 according to the embodiment.
  • the data transmitting device 2 includes a storage section 20, an input section 21, and a transmitting section 22.
  • each functional block of the data transmitting device 2 is assumed to function within the data transmitting device 2, it is not limited to this.
  • some of the functional blocks of the data transmitting device 2 are computer devices different from the data transmitting device 2, and are capable of transmitting and receiving information to and from the data transmitting device 2 as appropriate within a computer device connected to the data transmitting device 2 via a network. It is possible to function while doing so.
  • some functional blocks of the data transmitting device 2 may be omitted, multiple functional blocks may be integrated into one functional block, or one functional block may be decomposed into multiple functional blocks. good.
  • the storage section 20 and the input section 21 have the same functions as the storage section 10 and the input section 11 of the data aggregation device 1, respectively. Descriptions of similar functions will be omitted as appropriate.
  • the storage unit 20 stores arbitrary information used in calculations in the data transmitting device 2, results of calculations in the data transmitting device 2, and the like.
  • the storage unit 20 stores data held by the above-mentioned company B.
  • the information stored by the storage unit 20 may be appropriately referenced by each function of the data transmitting device 2.
  • the input unit 21 inputs data to be matched.
  • the data to be entered is associated with individuals and groups.
  • the input unit 21 inputs data stored by the storage unit 20 and owned by Company B.
  • FIG. 7 is a diagram showing an example of data held by Company B.
  • the data shown in FIG. 7 is position information for each user, which is position information of individuals for each group.
  • the location information for each user includes group 1 "Monday” whose group identifier is “Monday”, user identifier "aaa” and location information "area A" (individual identified by user identifier "aaa”).
  • Group 2 "Tuesday” includes a set of user identifier "aaa” and location information "Area C” and a set of user identifier "bbb” and location information "Area B". There is. That is, the user-specific location information is associated with individuals and groups. Note that in this embodiment, as an example of data held by Company B, user-specific location information including location information is employed, but the data is not limited to location information and may include any one or more arbitrary data. For example, in addition to a user identifier and location information, data regarding one or more attributes (eg, gender and age) of the individual identified by the user identifier may also be included.
  • attributes eg, gender and age
  • the input unit 21 generates and associates a matching identifier, which is an identifier that can identify individuals and groups of the data, with the input data.
  • FIG. 8 is a diagram showing an example of data in which a matching identifier is associated with the data shown in FIG. 7 (user-specific location information).
  • the input unit 21 generates a matching identifier "AAA$" from the user identifier "aaa” and the group identifier "Monday", for example, and associates it with the user-specific location information.
  • the input unit 21 generates a matching identifier "BBB$” from the user identifier "bbb” and the group identifier "Monday”, and generates a matching identifier "AAA” from the user identifier "aaa” and the group identifier "Tuesday”.
  • a matching identifier "BBB#” is generated from the user identifier "bbb” and the group identifier "Tuesday” and is associated with the user-specific location information.
  • the user-specific location information associated with matching identifiers includes a group 1 "Monday”, a set of matching identifier "AAA$” and location information "Area A”, and a matching identifier "BBB”.
  • Group 2 “Tuesday” includes a set of matching identifier “AAA#” and location information "Area C”, as well as matching identifier "BBB#” and location information. "Area B” etc. may also be included.
  • the input unit 21 may output the data associated with the matching identifier to the transmitting unit 22 or may cause the storage unit 20 to store the data.
  • the transmitting unit 22 sends the data associated with the matching identifier input from the input unit 21 or the data associated with the matching identifier stored by the storage unit 20 to (the counting unit 12 of) the data aggregating device 1. (for matching and aggregation).
  • the totaling unit 12 compares and totals the data associated with the matching identifiers for each group based on the matching identifiers.
  • the aggregation unit 12 aggregates the data for each group and calculates the aggregation results (aggregated data) for each group.
  • FIG. 9 is a diagram showing a scene in which the data shown in FIG. 5 and the data shown in FIG. 8 are compared and totaled.
  • group 1 "Monday"
  • the aggregation unit 12 matches the matching identifier included in the user list and the matching identifier included in the user-specific location information (data of the same matching identifier). aggregate (by counting, etc.) That is, the aggregation unit 12 aggregates data by day of the week. Note that both the day of the week (group) and the individual can be identified by the matching identifier. Furthermore, since the total results for each group can be identified, the degree of freedom in calculations described later is high.
  • the aggregation unit 12 may perform the aggregation using secure calculation.
  • the aggregation unit 12 may collate and aggregate the de-identified data. That is, the input unit 11 and the input unit 21 may input data that has been de-identified (in advance) (de-identification processing has been performed before inputting the data), or may de-identify the input data. .
  • de-identification refers to processing for eliminating easy collation between original data and de-identified data. Specifically, when assuming data in individual format, we assume irreversible conversion of key attribute information and processing to prevent re-identification from combinations of attribute information linked to key attributes, data structure, etc. However, it is not limited to this.
  • the aggregation unit 12 may output the calculated aggregated data for each group to the calculation unit 13 or may cause the storage unit 10 to store it.
  • the calculation unit 13 performs a predetermined calculation on the total results for each group (the total data for each group) by the total unit 12 (input by the total unit 12).
  • the predetermined calculation may be a calculation indicated by the calculation information input from the input unit 11 or may be a calculation indicated by the calculation information stored by the storage unit 10.
  • the predetermined calculation may be performed by integrating the aggregation results for each group by the aggregation unit 12.
  • the calculation unit 13 may pool aggregated data for each group and perform a predetermined calculation using all the data.
  • FIG. 10 is a diagram showing an example of aggregated data for each group.
  • the aggregated data shown in Figure 10 shows that there were 15 individuals located in Area A on Monday, 12 individuals located in Area B on Monday, and 38 individuals located in Area C on Monday. There are 12 individuals located in area A on Tuesday, 21 individuals located in area B on Tuesday, and 27 individuals located in area C on Tuesday. .
  • FIG. 11 is a diagram showing an example of aggregated data obtained by integrating aggregated data for each group (by a predetermined calculation).
  • the aggregated data shown in Figure 11 shows that during one week (Monday to Sunday), there were 105 individuals located in Area A, 251 individuals located in Area B, and 251 individuals located in Area C. This shows that there were 316 individuals who did so. Noise is added to the aggregated data shown in FIG. 11 by the concealment unit 14, which will be described later.
  • the calculation unit 13 may output aggregated data, which is the calculation result (integrated result) of a predetermined calculation, to the concealment unit 14 or may store it in the storage unit 10.
  • the concealment unit 14 conceals the integrated result of a predetermined calculation (by the calculation unit 13) by adding noise. More specifically, the concealment unit 14 adds noise that satisfies the differential privacy criteria (for example, adds a random value to the aggregate data input from the calculation unit 13 or the aggregate data stored by the storage unit 10). ) and generate statistics. For example, the concealment unit 14 adds noise to the calculation results using the day-of-week aggregate results. Since the concealing unit 14 adds noise to the calculation result (integrated result), the influence of noise can be reduced. The concealment unit 14 may perform concealment through secure calculation.
  • FIG. 12 is a diagram showing an example of statistical information in which noise is added to the integrated total data.
  • "-4" is added to the number of individuals located in area A
  • "19" is added to the number of individuals located in area B
  • the aggregated data shown in FIG. 11. is added, indicating that "-6" has been added to the number of individuals located in area C.
  • the concealment unit 14 may output the generated statistical information to the output unit 15 or may cause the storage unit 10 to store it.
  • the output unit 15 outputs the statistical information generated by the concealment unit 14 or the statistical information stored by the storage unit 10.
  • the output unit 15 may display the statistical information to the user of the data aggregation device 1 via an output device 1006, which will be described later, such as a display, or may transmit the statistical information to another device via a network.
  • the output unit 15 may output only the information that has been anonymized. That is, the output unit 15 may output only the information concealed by the concealment unit 14.
  • FIG. 13 is a sequence diagram illustrating an example of processing executed by the data aggregation system.
  • the input unit 11 of the data aggregation device 1 inputs data held by company A and associates it with a matching identifier (step S1).
  • the input unit 21 of the data transmitting device 2 inputs the data held by Company B, associates the data with a matching identifier, and transmits the data to the data aggregating device 1 by the transmitting unit 22 (Step S2). Note that the order of S1 and S2 may be reversed.
  • the aggregation unit 12 of the data aggregation device 1 sorts the data associated with the matching identifier in S1 and the data associated with the matching identifier in S2 into groups based on the matching identifiers. The data are compared and totaled to calculate total data for each group (step S3).
  • the calculation unit 13 of the data aggregation device 1 performs a predetermined operation on the group-by-group aggregate data calculated in S3, and calculates aggregate data that is the result of the operation (step S4).
  • the concealment unit 14 of the data aggregation device 1 conceals the total data calculated in S4 by adding noise, and generates statistical information (step S5).
  • the output unit 15 of the data aggregation device 1 outputs the statistical information generated in S5 (step S6).
  • the data aggregation device 1 has been described as having the aggregation unit 12, the calculation unit 13, the concealment unit 14, and the output unit 15, but the data transmission device 2 includes functional blocks having the same functions as these. You may prepare.
  • the data aggregation device 1 may include a functional block having the same function as the transmitting unit 22 included in the data transmitting device 2. That is, both the data aggregation device 1 and the data transmission device 2 may take the lead in performing processing such as comparison and aggregation. Thereby, both the data aggregation device 1 and the data transmission device 2 can perform processing interactively.
  • FIG. 14 is a diagram illustrating another example of processing executed by the data aggregation system.
  • FIG. 14 is a diagram illustrating the data input, matching identifier matching, aggregation, calculation, anonymization, and output, which have been explained so far, in order from the top.
  • the data aggregation device 1 is a device that collates and aggregates data that is owned by two or more organizations and is associated with individuals and groups
  • the aggregation unit 12 is a device that collates data that is held by two or more organizations and that is associated with individuals and groups.
  • Data associated with a matching identifier which is an identifier, is matched and totaled for each group based on the matching identifier. With this configuration, data is compared and totaled for each group based on the matching identifier. In other words, data can be matched for each group.
  • the data aggregation device 1 may further include a calculation unit 13 that performs predetermined calculations on the aggregation results for each group by the aggregation unit 12.
  • a calculation unit 13 that performs predetermined calculations on the aggregation results for each group by the aggregation unit 12.
  • the predetermined calculation may be a calculation specified in advance by the user. With this configuration, any calculation specified in advance by the user can be performed.
  • the predetermined calculation may be performed by integrating the results of the aggregation for each group by the aggregation unit 12. With this configuration, for example, one piece of data can be obtained as the integration result.
  • the data aggregation device 1 may further include a concealment unit 14 that conceals the integrated result of a predetermined calculation by adding noise to the result.
  • a concealment unit 14 that conceals the integrated result of a predetermined calculation by adding noise to the result.
  • the concealment unit 14 may conceal information through secure calculation. With this configuration, it is possible to conceal information in consideration of privacy.
  • the aggregation unit 12 may perform the aggregation using secure calculation. With this configuration, it is possible to perform aggregation taking privacy into consideration.
  • the aggregation unit 12 may collate and aggregate the de-identified data. With this configuration, it is possible to perform aggregation taking privacy into consideration.
  • a group may be a unit of aggregation when comparing data.
  • data can be more reliably aggregated for each aggregation unit when comparing data.
  • the data aggregation device 1 of the present disclosure has the following configuration.
  • a data aggregation device that collates and aggregates data held by two or more organizations and associated with individuals and groups, comprising a totaling unit that compares and totals the data associated with a matching identifier, which is an identifier that can identify the individual and the group, for each group based on the matching identifier; Data aggregation device.
  • the predetermined calculation is a calculation specified in advance by the user;
  • the predetermined calculation integrates the results of the aggregation for each group by the aggregation unit;
  • the data aggregation device according to [2] or [3].
  • the concealment unit performs concealment through secure calculation.
  • the data aggregation device according to [5].
  • the aggregation unit performs aggregation using secure calculation.
  • the data aggregation device according to any one of [1] to [6].
  • the aggregation unit collates and aggregates the de-identified data;
  • the data aggregation device according to any one of [1] to [7].
  • the group is an aggregation unit when comparing the data,
  • the data aggregation device according to any one of [1] to [8].
  • the usability is improved by aggregation using the matching identifier.
  • the challenge is to compare and aggregate data held by two (or more) organizations without disclosing the contents to each other, and to obtain aggregated results after adding noise that satisfies differential privacy standards to the aggregated results.
  • the challenge is to compare and aggregate data held by two (or more) organizations without disclosing the contents to each other, and to obtain aggregated results after adding noise that satisfies differential privacy standards to the aggregated results.
  • FIG. 15 is a diagram illustrating an example in which usefulness decreases due to the influence of noise.
  • n indicates noise.
  • FIG. 15 when calculations are performed using the aggregated results of each group, the influence of noise is large and the usefulness is reduced.
  • the data aggregation device 1 generates a matching identifier from a group identifier that identifies a group to be matched and a user identifier, thereby making it possible to perform aggregation for each group and arbitrary calculations using the aggregation results for each group. . According to such a data aggregation device 1, it is possible to improve the usefulness when performing calculations using the aggregation results of multiple groups.
  • FIG. 16 is a diagram illustrating a problem when aggregation is performed separately for each group. As shown in FIG. 16, noise is added to the aggregation results in each group during the concealment process, which reduces the usefulness.
  • FIG. 17 is a diagram illustrating problems when generating matching identifiers and merging data of a plurality of groups. As shown in FIG. 17, calculations other than summation cannot be performed, and the degree of freedom is low.
  • data aggregation device 1 compared to (2), noise is minimized and usefulness is improved, and unlike (3), groups can be identified after aggregation, so group aggregation results are used. Calculations (for example, the average of group aggregated results) can be taken.
  • each functional block may be realized using one physically or logically coupled device, or may be realized using two or more physically or logically separated devices directly or indirectly (e.g. , wired, wireless, etc.) and may be realized using a plurality of these devices.
  • the functional block may be realized by combining software with the one device or the plurality of devices.
  • Functions include judgment, decision, judgment, calculation, calculation, processing, derivation, investigation, exploration, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, These include, but are not limited to, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assigning. I can't do it.
  • a functional block (configuration unit) that performs transmission is called a transmitting unit or a transmitter. In either case, as described above, the implementation method is not particularly limited.
  • the data aggregation device 1 in an embodiment of the present disclosure may function as a computer that performs processing of the data aggregation method of the present disclosure.
  • FIG. 18 is a diagram illustrating an example of the hardware configuration of the data aggregation device 1 according to an embodiment of the present disclosure.
  • the data aggregation device 1 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like.
  • the word “apparatus” can be read as a circuit, a device, a unit, etc.
  • the hardware configuration of the data aggregation device 1 may be configured to include one or more of each device shown in the figure, or may be configured without including some of the devices.
  • Each function in the data aggregation device 1 is performed by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, so that the processor 1001 performs calculations, controls communication by the communication device 1004, and controls the memory This is realized by controlling at least one of reading and writing data in the storage 1002 and the storage 1003.
  • the processor 1001 for example, operates an operating system to control the entire computer.
  • the processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, registers, and the like.
  • CPU central processing unit
  • the input section 11, aggregation section 12, calculation section 13, concealment section 14, output section 15, etc. described above may be realized by the processor 1001.
  • the processor 1001 reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 to the memory 1002, and executes various processes in accordance with these.
  • programs program codes
  • the program a program that causes a computer to execute at least part of the operations described in the above embodiments is used.
  • the input unit 11, aggregation unit 12, calculation unit 13, concealment unit 14, and output unit 15 may be realized by a control program stored in the memory 1002 and operated in the processor 1001, and the same applies to other functional blocks. may be realized.
  • the various processes described above have been described as being executed by one processor 1001, they may be executed by two or more processors 1001 simultaneously or sequentially.
  • Processor 1001 may be implemented by one or more chips. Note that the program may be transmitted from a network via a telecommunications line.
  • the memory 1002 is a computer-readable recording medium, and includes at least one of ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. may be done.
  • Memory 1002 may be called a register, cache, main memory, or the like.
  • the memory 1002 can store executable programs (program codes), software modules, and the like to implement a wireless communication method according to an embodiment of the present disclosure.
  • the storage 1003 is a computer-readable recording medium, such as an optical disk such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, or a magneto-optical disk (for example, a compact disk, a digital versatile disk, or a Blu-ray disk). (registered trademark disk), smart card, flash memory (eg, card, stick, key drive), floppy disk, magnetic strip, etc.
  • Storage 1003 may also be called an auxiliary storage device.
  • the storage medium mentioned above may be, for example, a database including at least one of memory 1002 and storage 1003, a server, or other suitable medium.
  • the communication device 1004 is hardware (transmission/reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc., for example.
  • the communication device 1004 includes, for example, a high frequency switch, a duplexer, a filter, a frequency synthesizer, etc. in order to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). It may be composed of.
  • FDD frequency division duplex
  • TDD time division duplex
  • FDD frequency division duplex
  • TDD time division duplex
  • It may be composed of.
  • the above-described input unit 11, aggregation unit 12, calculation unit 13, concealment unit 14, output unit 15, etc. may be realized by the communication device 1004.
  • the input device 1005 is an input device (eg, keyboard, mouse, microphone, switch, button, sensor, etc.) that accepts input from the outside.
  • the output device 1006 is an output device (for example, a display, a speaker, an LED lamp, etc.) that performs output to the outside. Note that the input device 1005 and the output device 1006 may have an integrated configuration (for example, a touch panel).
  • each device such as the processor 1001 and the memory 1002 is connected by a bus 1007 for communicating information.
  • the bus 1007 may be configured using a single bus, or may be configured using different buses for each device.
  • the data aggregation device 1 also includes hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), and a field programmable gate array (FPGA).
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • PLD programmable logic device
  • FPGA field programmable gate array
  • a part or all of each functional block may be realized by the hardware.
  • processor 1001 may be implemented using at least one of these hardwares.
  • LTE Long Term Evolution
  • LTE-A Long Term Evolution-Advanced
  • SUPER 3G IMT-Advanced
  • 4G 4th generation mobile communication system
  • 5G 5th generation mobile communication system
  • FRA Fluture Radio Access
  • NR new Radio
  • W-CDMA registered trademark
  • GSM registered trademark
  • CDMA2000 Code Division Multiple Access 2000
  • UMB Universal Mobile Broadband
  • IEEE 802.11 Wi-Fi (registered trademark)
  • IEEE 802.16 WiMAX (registered trademark)
  • IEEE 802.20 UWB (Ultra-WideBand
  • Bluetooth registered trademark
  • a combination of a plurality of systems may be applied (for example, a combination of at least one of LTE and LTE-A and 5G).
  • the input/output information may be stored in a specific location (for example, memory) or may be managed using a management table. Information etc. to be input/output may be overwritten, updated, or additionally written. The output information etc. may be deleted. The input information etc. may be transmitted to other devices.
  • Judgment may be made using a value expressed by 1 bit (0 or 1), a truth value (Boolean: true or false), or a comparison of numerical values (for example, a predetermined value). (comparison with a value).
  • notification of prescribed information is not limited to being done explicitly, but may also be done implicitly (for example, not notifying the prescribed information). Good too.
  • Software includes instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, whether referred to as software, firmware, middleware, microcode, hardware description language, or by any other name. , should be broadly construed to mean an application, software application, software package, routine, subroutine, object, executable, thread of execution, procedure, function, etc.
  • software, instructions, information, etc. may be sent and received via a transmission medium.
  • a transmission medium For example, if the software uses wired technology (coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), etc.) and/or wireless technology (infrared, microwave, etc.) to create a website, When transmitted from a server or other remote source, these wired and/or wireless technologies are included within the definition of transmission medium.
  • wired technology coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), etc.
  • wireless technology infrared, microwave, etc.
  • data, instructions, commands, information, signals, bits, symbols, chips, etc. which may be referred to throughout the above description, may refer to voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any of these. It may also be represented by a combination of
  • system and “network” are used interchangeably.
  • information, parameters, etc. described in this disclosure may be expressed using absolute values, relative values from a predetermined value, or using other corresponding information. may be expressed.
  • determining may encompass a wide variety of operations.
  • “Judgment” and “decision” include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, search, and inquiry. (e.g., searching in a table, database, or other data structure), and regarding an ascertaining as a “judgment” or “decision.”
  • judgment and “decision” refer to receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, and access.
  • (accessing) may include considering something as a “judgment” or “decision.”
  • judgment and “decision” refer to resolving, selecting, choosing, establishing, comparing, etc. as “judgment” and “decision”. may be included.
  • judgment and “decision” may include regarding some action as having been “judged” or “determined.”
  • judgment (decision) may be read as "assuming", “expecting", “considering”, etc.
  • connection means any connection or coupling, direct or indirect, between two or more elements and each other. It may include the presence of one or more intermediate elements between two elements that are “connected” or “coupled.”
  • the bonds or connections between elements may be physical, logical, or a combination thereof. For example, "connection” may be replaced with "access.”
  • two elements may include one or more electrical wires, cables, and/or printed electrical connections, as well as in the radio frequency domain, as some non-limiting and non-inclusive examples. , electromagnetic energy having wavelengths in the microwave and optical (both visible and non-visible) ranges.
  • the phrase “based on” does not mean “based solely on” unless explicitly stated otherwise. In other words, the phrase “based on” means both “based only on” and “based at least on.”
  • any reference to elements using the designations "first,” “second,” etc. does not generally limit the amount or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Thus, reference to a first and second element does not imply that only two elements may be employed or that the first element must precede the second element in any way.
  • a and B are different may mean “A and B are different from each other.” Note that the term may also mean that "A and B are each different from C”. Terms such as “separate” and “coupled” may also be interpreted similarly to “different.”

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