Information processing device, generation method, and generation program

Abstract

An information processing device (10) comprises a collection unit (15B) that collects answers to a questionnaire which is set on the basis of a combination of a first item relating to the information type of personal information targeted for a privacy policy and a second item relating to handling of the personal information, and a generation unit (15D) that generates a privacy policy corresponding to the answers to the questionnaire.

Description

Information processing device, generation method, and generation program

[0001] The present invention relates to an information processing device, a generation method, and a generation program.

[0002] When using services, etc., legal requirements such as the Personal Information Protection Act require users to understand and agree to the privacy policies presented by service providers such as companies.

[0003] Personal Data Dashboard, [Retrieved July 12, 2024], Internet <URL: https: / / datadashboard.front.smt.docomo.ne.jp / > Daniel Reinhardt, Johannes Borchard, Joern Hurtienne “Visual Interactive Privacy Policy: The Better Choice?” CHI2021, May 8-13, 2021

[0004] However, the above-mentioned privacy policy is a one-sided expression of the service provider's opinion, and there is room for improvement in that users are only given the choice of whether or not to use the service.

[0005] Therefore, an object of the present invention is to provide an information processing device, a generation method, and a generation program that can realize the generation of a privacy policy that reflects user opinions.

[0006] In order to solve the above-mentioned problems and achieve the objectives, the information processing device of the present invention has a collection unit that collects responses to a questionnaire set based on a combination of a first item regarding the information type of personal information that is the subject of the privacy policy and a second item regarding the handling of the personal information, and a generation unit that generates a privacy policy corresponding to the responses to the questionnaire.

[0007] According to the present invention, it is possible to generate a privacy policy that reflects the opinions of users.

[0008] FIG. 1 is a block diagram illustrating an example of the functional configuration of an information processing device. FIG. 2 is a diagram illustrating an example of input / output relationships between functional blocks. FIG. 3 is a flowchart illustrating the processing procedure of a questionnaire presentation unit. FIG. 4 is a diagram illustrating an example of a questionnaire type selection screen. FIG. 5 is a diagram illustrating an example of a full questionnaire master. FIG. 6 is a diagram illustrating an example of a questionnaire screen (1). FIG. 7 is a diagram illustrating an example of a simple questionnaire master. FIG. 8 is a diagram illustrating an example of a questionnaire screen (2). FIG. 9 is a flowchart illustrating the processing procedure of a response collection unit. FIG. 10 is a flowchart illustrating the processing procedure of a score calculation unit. FIG. 11 is a diagram illustrating an example of a method for classifying user types. FIG. 12 is a flowchart illustrating the processing procedure of a privacy policy generation unit. FIG. 13 is a diagram illustrating an example of a user privacy policy (1). FIG. 14 is a diagram illustrating an example of a user privacy policy (2). FIG. 15 is a flowchart illustrating the processing procedure of a correction unit. FIG. 16 is a diagram illustrating an example of a change to a user privacy policy. FIG. 17 is a diagram illustrating an example of a management table. FIG. 18 is a diagram illustrating an example of a user policy response table. FIG. 19 is a flowchart illustrating the processing procedure of an update detection unit. FIG. 20 is a diagram illustrating an example of a hardware configuration.

[0009] Hereinafter, an information processing device, a generation method, and a generation program according to the present application (hereinafter referred to as an "embodiment") will be described with reference to the accompanying drawings. Note that this embodiment merely illustrates one example or one aspect, and the following description does not limit the structure, action, function, properties, characteristics, methods, uses, etc. according to the present disclosure.

[0010] <Use Case> Fig. 1 is a block diagram showing an example of the functional configuration of an information processing device 10. Fig. 1 shows the information processing device 10 that provides a generation function for generating a privacy policy, particularly a privacy policy that reflects user opinions.

[0011] Hereinafter, to distinguish between the user-driven privacy policy generated by the generation function described above and the privacy policy listed in the background art section above, the former may be referred to as the "user privacy policy."

[0012] Furthermore, a service provider will be taken as an example of a customer of the above-mentioned generation function, and a use case will be taken as an example in which the above-mentioned generation function is provided at the start of a service in which a consumer user, a so-called end user, starts using a service provided by the service provider.

[0013] <Overall Configuration> In one aspect, the information processing device 10 may be realized by a server device. For example, the information processing device 10 can provide the above-described generation function as a cloud service by executing PaaS (Platform as a Service) type middleware or SaaS (Software as a Service) type application.

[0014] 1, the information processing device 10 can be communicatively connected to a user terminal 30 via a network NW. For example, the network NW may be realized by any type of communication network, such as the Internet or a local area network (LAN), whether wired or wireless.

[0015] The user terminal 30 is a terminal device used by the user. For example, the user terminal 30 may be realized by any computer, such as a personal computer, a smartphone, a tablet terminal, or a wearable terminal.

[0016] Although the above generation function is provided as a cloud service, the present invention is not limited to this. For example, the generation function may be provided on-premise. Furthermore, the generation function may be packaged as one function of a service or application provided by the service provider.

[0017] Although the above-described generation function is implemented as a client-server system, the present invention is not limited to this. For example, the generation function may be provided as a standalone function by causing an application running on the user terminal 30 to execute processing corresponding to the generation function on the user terminal 30.

[0018] <Configuration of Information Processing Device 10> Next, the functional configuration of the information processing device 10 that provides the above-mentioned generation function will be described using Figures 1 and 2. For example, Figure 1 schematically shows functional blocks related to the generation function of the information processing device 10. Figure 2 is a diagram showing an example of the input / output relationship between the functional blocks. Figure 2 shows the input / output relationship between the functional blocks shown in Figure 1.

[0019] 1, the information processing device 10 includes a communication control unit 11, a storage unit 13, and a control unit 15. Note that Fig. 1 only shows a selection of functional units related to the above-described generation function, and the information processing device 10 may include functional units other than those shown in the figure.

[0020] The communication control unit 11 is a functional unit that controls communication with other devices, such as the user terminal 30 or a server device (not shown) of a service provider that provides web services. In one embodiment, the communication control unit 11 can be realized by a network interface card such as a LAN card. In one aspect, the communication control unit 11 accepts a generation request for generating a user privacy policy from the user terminal 30 or the server device of the service provider. In another aspect, the communication control unit 11 outputs a response to the request, such as a generated user privacy policy, to the user terminal 30 or the server device of the service provider.

[0021] The storage unit 13 is a functional unit that stores various types of data. In one embodiment, the storage unit 13 may be realized by internal, external, or auxiliary storage of the information processing device 10. For example, the storage unit 13 stores a survey database (DB) 13A and a privacy policy DB 13B. The data in the survey DB 13A and the privacy policy DB 13B will be described later together with the scenes in which the data are referenced.

[0022] The control unit 15 is a functional unit that performs overall control of the information processing device 10. For example, the control unit 15 may be realized by a hardware processor. As shown in FIG. 1 , the control unit 15 includes a questionnaire presentation unit 15A, a response collection unit 15B, a score calculation unit 15C, a privacy policy generation unit 15D, a correction unit 15E, and an update detection unit 15F. Note that the control unit 15 may also be realized by hardwired logic or the like.

[0023] <Survey Presentation Unit> The questionnaire presentation unit 15A is a processing unit that presents a questionnaire used to generate the above-described user privacy policy to the user terminal 30. In one aspect, as shown in Fig. 2, the questionnaire presentation unit 15A receives as input data a generation request requesting generation of a user privacy policy and a selection of a questionnaire type, and outputs as output data a questionnaire screen including questions related to the questionnaire items.

[0024] An example of a situation in which such a generation request is received is when the user starts using an application installed on the user terminal 30 and the above generation request is received from the application via a browser. Hereinafter, an application program may be referred to as "APP." Another example is when the above generation function is called via API (Application Programming Interface) collaboration from a server device of a service provider that provides a web service when the user starts using a web service in general.

[0025] 3 is a flowchart showing the processing procedure of the questionnaire presenting unit 15A. This processing can be started when the above-mentioned generation request is accepted, as an example. As shown in FIG. 3, the questionnaire presenting unit 15A accepts the selection of a questionnaire type via the browser 31 (see FIG. 2) (step S101).

[0026] Such a questionnaire type can be selected by displaying a GUI (Graphical User Interface) such as a questionnaire type selection screen shown in FIG. 4 on the user terminal 30, as an example only.

[0027] 4 is a diagram showing an example of a questionnaire type selection screen. As shown in FIG. 4, the questionnaire type selection screen includes a message prompting the user to select whether to respond to the full version questionnaire or the simplified version questionnaire. Hereinafter, the full version questionnaire may be referred to as a "full questionnaire," and the simplified version questionnaire may be referred to as a "simple questionnaire."

[0028] Here, the questionnaire refers to questions about the user privacy policy. For example, the questionnaire may be set based on a combination of a first item about the type of personal information covered by the user privacy policy and a second item about the handling of the personal information.

[0029] As an example of the handling of personal information, we will use the "purpose of use" that a service provider handling personal information clearly indicates to the user, the subject of the information, for what purpose the service provider will use the data collected as personal information.

[0030] Of these, the "full questionnaire" may be a question that asks respondents to choose whether or not to consent to the use of their personal information for each questionnaire item determined by a combination of a first item related to the type of information and a second item related to the purpose of use. For example, consider a sample obtained from a survey of the privacy policies of 108 existing websites. If the survey results show that there are 21 first items related to the type of information and 6 second items related to the purpose of use, the total number of questionnaire items corresponding to the combination of the first and second items will be 126.

[0031] On the other hand, the "simplified questionnaire" may be a questionnaire with fewer questions than the full questionnaire described above. Such a simplified questionnaire may include a question assessing privacy concerns regarding a combination of a first item related to information type and a second item related to the purpose of use. For example, a series of answers included in the full questionnaire may be categorized into a specific number of user types in advance, i.e., the number of information types × the number of purposes of use × the number of answer options (= 21 × 6 × 2), and questionnaire items leading to each user type may be set. Such questionnaire items may be based on a model such as the IUIPC (Internet User's Information Privacy Concerns) for assessing privacy concerns, e.g., IUIPC-8.

[0032] 3, a selection can be made between two types of questionnaires, a full questionnaire and a simple questionnaire. Note that the number of types of questionnaires is merely an example, and may be one, three, or more.

[0033] At this time, if the full questionnaire is selected (Yes in step S102), the questionnaire presenting unit 15A generates a questionnaire screen based on the full questionnaire master included in the questionnaire DB 13A stored in the storage unit 13 (step S103).

[0034] 5 is a diagram showing an example of the full questionnaire master 13A1. As shown in Fig. 5, the full questionnaire master 13A1 may be data in which items such as "No.", "Information type x Purpose of use", "Question content", "Check period", "Check destination", "Last update date and time", and "Revision necessary confirmation flag" are associated with each other.

[0035] Here, "No." refers to a number that identifies a record in the full survey master, and may be a sequential number, for example. Furthermore, "information type x purpose of use" refers to identification information that identifies the individual and composition of a survey item, and may be identified, for example, by a combination of information type identification information and purpose of use identification information. For example, FIG. 5 shows an example in which a first item related to information type is identified by a sequential number, such as 1, 2, ..., M (natural numbers), and a second item related to purpose of use is identified by a single capital letter. In this numbering example, in the first row shown in FIG. 5 , the individual and composition of a survey item are indicated by the combination "1A" of the number "1" corresponding to the information type "location information" and the letter "A" corresponding to the purpose of use "to provide services." Furthermore, "question content" refers to the content of questions related to the survey item. Furthermore, "check period" refers to the period for checking for amendments to the law governing the establishment of a user privacy policy, such as the Personal Information Protection Act. Furthermore, "check destination" refers to the destination for checking for amendments. The "last updated date and time" indicates the date and time when the record of the questionnaire item was last updated. The "revision necessity confirmation flag" indicates a flag used to confirm whether revision is necessary.

[0036] According to such a full questionnaire master 13A1, it is possible to generate a questionnaire screen as shown in Fig. 6. Fig. 6 is a diagram (1) showing an example of the questionnaire screen. As shown in Fig. 6, the questionnaire screen may include, for each questionnaire item, a message corresponding to a question regarding the questionnaire item and GUI components corresponding to two answers, "OK" corresponding to agreement and "NG" corresponding to disagreement, arranged thereon.

[0037] 6 shows three survey items selected from a total of 126 survey items, but it goes without saying that responses to the remaining survey items can be received by scrolling the screen or switching pages, etc. Also, while FIG. 6 shows an example in which the response options include two options, "agree" or "disagree," other options such as "neither" or "may agree under certain conditions" may also be included.

[0038] Returning to the explanation of Figure 3, if a simple questionnaire is selected (No in step S102), the questionnaire presentation unit 15A generates a questionnaire screen based on the simple questionnaire master contained in the questionnaire DB 13A stored in the memory unit 13 (step S104).

[0039] Fig. 7 is a diagram showing an example of the simplified questionnaire master 13A2. As shown in Fig. 7, the simplified questionnaire master 13A2 shows questions related to eight questionnaire items corresponding to IUIPC-8, which is an example of the IUIPC model for assessing privacy concerns. According to such simplified questionnaire master 13A2, it is possible to generate the questionnaire screen shown in Fig. 8.

[0040] FIG. 8 is a diagram (2) showing an example of a questionnaire screen. As shown in FIG. 8, the questionnaire screen may include a message corresponding to a question regarding a questionnaire item and a GUI component with five levels of agreement or disagreement with the question. For example, in the example shown in FIG. 8, GUI components representing "True," "Somewhat True," "Neutral," "Somewhat Disagree," and "Disagree" are arranged in descending order of agreement with the question, "1. Online consumer privacy is a matter of consumers' right to exercise control and autonomy over how their information is collected, used, and shared." Note that while FIG. 8 illustrates an example of one of the eight questionnaire items corresponding to IUIPC-8, a five-level rating of agreement can also be accepted for the other questionnaire items.

[0041] Thereafter, the questionnaire presenting unit 15A outputs the questionnaire screen, for example, the full questionnaire or the simple questionnaire, generated in the above step S103 or step S104 to the user terminal 30 (step S105), and ends the process.

[0042] <Response Collection Unit> The response collection unit 15B is a processing unit that collects responses to the above questionnaire. Fig. 9 is a flowchart showing the processing procedure of the response collection unit. As shown in Fig. 9, the response collection unit 15B collects responses to the full questionnaire or simple questionnaire from the user terminal 30 (step S201), and then ends the processing.

[0043] <Score Calculation Unit> The score calculation unit 15C is a processing unit that calculates a score for evaluating privacy concerns based on the answers included in the questionnaire. In one aspect, the score calculation unit 15C receives the answers to the simple questionnaire as input data and outputs a user type classified based on the answers to the simple questionnaire.

[0044] 10 is a flowchart showing the processing procedure of the score calculation unit 15C. As shown in Fig. 10, if the questionnaire collected by the response collection unit 15B is a simple questionnaire (Yes in step S301), the score calculation unit 15C calculates a score that evaluates the degree of privacy concern of the user based on the responses to the simple questionnaire (step S302).

[0045] As just one example, the score calculation unit 15C can derive the above score by calculating a statistical value, such as an average value, of the agreement levels of the questionnaire items included in the simple questionnaire. For example, as in the example described above, if each questionnaire item in the simple questionnaire accepts an agreement level on a five-point scale, the numerical range of the arithmetic mean of the scores will be from a lower limit of "1" to an upper limit of "5." Note that while an example of calculating an arithmetic mean has been given here, a weighted mean can also be calculated by assigning different weights to the questionnaire items, or other statistical values, such as the median or mode, can also be calculated as the score.

[0046] Next, the score calculation unit 15C classifies the user who sent the generation request into the user type corresponding to the score calculated in step S302 (step S303), and ends the process.

[0047] FIG. 11 is a diagram showing an example of a method for classifying user types. FIG. 11 illustrates three user types: data unconcerned, data pragmatist, and data fundamentalist. As shown in FIG. 11 , if the score calculated in step S302 falls within a numerical range of 1 or greater and less than 2, the user who sent the generation request is classified as a "data unconcerned." Furthermore, if the score calculated in step S302 falls within a numerical range of 2 or greater and less than 4, the user who sent the generation request is classified as a "data pragmatist." Furthermore, if the score calculated in step S302 falls within a numerical range of 4 or greater and less than 5, the user who sent the generation request is classified as a "data fundamentalist." In this way, users can be classified into three types depending on their scores.

[0048] 11 shows an example in which users are classified into three user types, but the number of user types is not limited to three, and users can be classified into any number of user types equal to or greater than two. Also, while Figures 10 and 11 show an example in which users are classified into user types corresponding to scores that evaluate the degree of privacy concerns, users can also be classified into user types corresponding to patterns of demographic data, such as age, sex, place of residence, family structure, and occupation.

[0049] <Privacy Policy Generation Unit> The privacy policy generation unit 15D is a processing unit that generates a user privacy policy corresponding to the responses to the questionnaire. In one aspect, the privacy policy generation unit 15D receives the responses to the full questionnaire collected by the response collection unit 15B or the user type classified by the score calculation unit 15C as input data, and outputs the user privacy policy as output data.

[0050] 12 is a flowchart showing the processing procedure of the privacy policy generation unit 15D. As shown in Fig. 12, when responses to the full questionnaire have been collected (Yes in step S401), the privacy policy generation unit 15D generates a user privacy policy corresponding to the responses to the full questionnaire (step S402).

[0051] That is, in step S402, the responses to each questionnaire item included in the questionnaire screen shown in FIG. 6 are reflected as a user privacy policy. FIG. 13 is a diagram (1) showing an example of a user privacy policy. As shown in FIG. 13, the privacy policy generation unit 15D can generate a user privacy policy in which the selection results of "agree" or "disagree" answered for each questionnaire item included in the full questionnaire are associated. For example, in the example shown in FIG. 13, the user privacy policy may be expressed in a table format in which first items related to information types identified by numbers are arranged in columns and second items related to purposes of use identified by letters are arranged in rows. Furthermore, a GUI component such as a toggle button indicating an "agree" or "disagree" response may be placed in the cell corresponding to each questionnaire item.

[0052] 13, it can be seen that the user has expressed consent to the questionnaire items 1B "Use of location information for fraud detection and security purposes" and 2A "Use of biometric information for service provision." As another aspect, it can be seen that the user has expressed disagreement to the questionnaire items 1A "Use of location information for service provision" and 2B "Use of biometric information for fraud detection and security purposes."

[0053] On the other hand, if responses to the simple questionnaire have been collected (No in step S401), the privacy policy generation unit 15D generates a user privacy policy corresponding to the user type classified by the score calculation unit 15C (step S403).

[0054] That is, in the above step S403, response patterns for each questionnaire item in the full questionnaire are set for each of the three user types shown in FIG. 11, and a user privacy policy is generated according to the response patterns corresponding to the user types classified by the score calculation unit 15C.

[0055] FIG. 14 is a diagram (2) showing an example of a user privacy policy. FIG. 14 illustrates example response patterns for each of the three user types shown in FIG. 11: data indifferent, data pragmatist, and data fundamentalist. As shown in FIG. 14, data indifferent is assigned a response pattern indicating agreement with all survey items. Data pragmatists are assigned a response pattern indicating disagreement with advertising uses that may push unnecessary information, but agreement with effective uses such as service provision, fraud detection, and security. Data fundamentalists are assigned a response pattern indicating disagreement with all survey items except for fraud detection and security, which are risk prevention survey items. In this way, even with a simplified survey with eight questions reduced compared to a full survey, a user privacy policy can be generated that reflects the user's intentions for the corresponding type.

[0056] Thereafter, the privacy policy generation unit 15D outputs a privacy policy screen including the user privacy policy generated in step S402 or step S403 to the user terminal 30 (step S404), and ends the process.

[0057] Note that Figures 13 and 14 show the purpose of use as an example of handling personal information, but other handling of personal information, such as collection method, storage method, and consent or non-consent to provision to third parties, can also be generated in the same way as the purpose of use.

[0058] <Modification Unit> Modification unit 15E is a processing unit that modifies the user privacy policy based on a change operation on the user privacy policy generated by privacy policy generation unit 15 D. In one aspect, modification unit 15E uses a change operation on a questionnaire item included in the user privacy policy as input data, and uses the modified user privacy policy as output data.

[0059] Fig. 15 is a flowchart showing the processing procedure of the correction unit 15E. As shown in Fig. 15, the correction unit 15E receives a report on the user privacy policy generated by the privacy policy generation unit 15D, such as questions or unclear points (step S501).

[0060] Then, when an operation to change the user privacy policy is received (Yes at step S502), the modifying unit 15E modifies the user privacy policy in accordance with the operation to change the user privacy policy (step S503).

[0061] FIG. 16 is a diagram showing an example of a change to the user privacy policy. FIG. 16 shows an example in which a change operation to the user privacy policy shown in FIG. 13 is accepted. For example, in the example shown in FIG. 16, a toggle button switch placed in the cell of questionnaire item 2B, "Use of biometric information for fraud detection and security," among the questionnaire items included in the user privacy policy, is accepted as a change operation. In this case, the intention regarding questionnaire item 2B, "Use of biometric information for fraud detection and security," is amended from "disagree" to "agree." This allows for an amendment that reflects the user's opinion, for example, "biometric information can be used for anything."

[0062] Thereafter, when a registration operation for a user privacy policy is accepted (Yes in step S504), the modifying unit 15E executes the following process: The modifying unit 15E registers the user privacy policy that is set at the time when the registration operation is accepted in the privacy policy DB 13B stored in the storage unit 13 (step S505).

[0063] As just one example, the privacy policy DB 13B may be realized by a management table 13B1 that manages metadata of user privacy policies and a user policy response table 13B2 that manages data of the main body of the user privacy policies.

[0064] FIG. 17 is a diagram illustrating an example of the management table 13B1. As illustrated in FIG. 17, the management table 13B1 may contain data in which items such as "ID (Identification)," "User," "UPID," "Creation Date and Time," and "Creation Type" are associated with each other. Among these, "ID" is an identifier for identifying a record in the management table 13B1. "User" refers to a user name. "UPID" refers to an ID for identifying a user privacy policy. "Creation Date and Time" refers to the date and time the user privacy policy was created. "Creation Type" refers to the type of questionnaire used to create the user privacy policy. For example, a user privacy policy created using a simple questionnaire may be registered as "Lite," while a user privacy policy created using a full questionnaire may be registered as "Full." This management table 13B1 enables chronological management of user privacy policies for the same user, as well as detection and output of differences between user privacy policies between two points in time.

[0065] FIG. 18 is a diagram showing an example of the user policy response table 13B2. As shown in FIG. 18, the user policy response table 13B2 may be data in which items such as "UPID," "information type x purpose of use (= questionnaire item ID)," and "answer" are associated with each other. Among these, "answer" refers to a response to a questionnaire item. For example, if the user agrees, "0 (= OK)" is stored; if the user disagrees, "1 (= NG)" is stored; and if the user does not respond, "2 (= NA (Not Applicable))" is stored. For example, FIG. 18 shows an excerpt of a response to a user privacy policy created by user "Taro" on December 15, 2023. In the example of the first line, this indicates that consent has been obtained for questionnaire item 1A, "Using location information to provide services."

[0066] Furthermore, the modifying unit 15E outputs the user privacy policy to the user terminal 30 (step S506), and ends the process. Note that the user privacy policy output to the user terminal 30 can be saved in a store accessible by the browser 31, so that it can be presented to other service providers when the user starts using other services.

[0067] <Update Detection Unit> The update detection unit 15F is a processing unit that detects an update of the provision related to each first item related to an information type that is the target of the user privacy policy. In one aspect, the update detection unit 15F can start processing independently of a series of sequences from receiving a request to generate the user privacy policy to generating the user privacy policy.

[0068] In one aspect, the update detection unit 15F can be activated at a specific interval using a timer, etc. In another aspect, the update detection unit 15F can also be activated by receiving an update notification such as an RSS (Rich Site Summary) from a website that is set as a check destination for a survey item included in the full survey master 13A1 of the survey DB 13A.

[0069] Fig. 19 is a flowchart showing the processing procedure of the update detection unit 15F. For example, Fig. 19 shows, as an example only, a procedure in which the update detection unit 15F starts processing using a timer at the check period set in the full questionnaire master 13A1 shown in Fig. 5, and detects, by referring to the check destination, whether or not a web page related to the law governing the establishment of a privacy policy, such as an amendment to the Personal Information Protection Act, has been updated for each questionnaire item.

[0070] 19, the update detection unit 15F executes loop process 1, which repeats the processes from step S601 to step S604 described below a number of times corresponding to the number N of questionnaire items for which the timer measurement value reaches the check period among the questionnaire items set in the full questionnaire master 13A1 shown in Fig. 5. Note that the processes from step S601 to step S604 described below may be executed in parallel for each of the N questionnaire items.

[0071] That is, the update detection unit 15F executes web crawling by referring to the check destination corresponding to the question content of the n-th questionnaire item (step S601). Then, the update detection unit 15F determines whether the web page obtained by the web crawling in step S601 satisfies a specified condition (step S602).

[0072] As an example, the update detection unit 15F determines whether a specific keyword, such as a character string related to an amendment or its content, is searched for in the HTML (HyperText Markup Language) source obtained by web crawling. In this case, one keyword or multiple keywords may be set as the keyword to be searched. For example, when multiple keywords are set, an AND condition or an OR condition may be set as the search condition for the multiple keywords.

[0073] Here, if the web page obtained by web crawling satisfies the specified conditions (Yes in step S602), the update detection unit 15F sets the revision necessity confirmation flag of the nth questionnaire item to 1 (= confirmation required) (step S603).

[0074] On the other hand, if the web page obtained by web crawling does not satisfy the specified conditions (No in step S602), the update detection unit 15F sets the revision necessity confirmation flag of the nth questionnaire item to 0 (= latest) (step S604).

[0075] By repeating this loop process 1, a confirmation flag for whether revision is necessary can be set for each of the N survey items. This makes it possible to detect whether an operation is necessary to determine whether the provisions of the user privacy policy should be changed due to the revision for each of the N survey items.

[0076] As described above, the information processing device 10 according to this embodiment collects responses to a questionnaire set based on a combination of a first item related to the type of personal information to be covered by the privacy policy and a second item related to the handling of the personal information, and generates a privacy policy corresponding to the responses to the questionnaire. Therefore, the information processing device 10 according to this embodiment can generate a privacy policy that reflects the user's opinions.

[0077] <Exercising Creative Ability> For example, the matters described in this embodiment, such as specific examples of various items such as information type and purpose of use, and further specific examples such as DBs stored in the information processing device 10 and screens output to the user terminal 30, are merely examples and can be changed. Furthermore, the order of processes in the flowchart described in this embodiment can also be changed or some processes can be skipped within a consistent range.

[0078] <System> The information including the processing procedures, control procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, any one or more of the functional units among the questionnaire presentation unit 15A, response collection unit 15B, score calculation unit 15C, privacy policy generation unit 15D, correction unit 15E, and update detection unit 15F of the information processing device 10 may be configured as separate devices.

[0079] Furthermore, the components of each device shown in the figure are functional concepts and do not necessarily have to be physically configured as shown. In other words, the specific form of distribution and integration of each device is not limited to that shown. In other words, all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc. Note that each configuration may also be a physical configuration.

[0080] Furthermore, all or any part of the processing performed by the illustrated device may be realized by a program executed by a hardware processor such as an MPU (Micro-Processing Unit) or a CPU (Central Processing Unit), or may be realized as hardware using wired logic.

[0081] <Hardware> Next, an example of the hardware configuration of the information processing device 10 described in this embodiment will be described. For example, the information processing device 10 can be implemented by installing a program that realizes the functions of the information processing device 10 on a computer. For example, the information processing device 10 can be implemented by having the computer execute the program, which is provided as package software or online software. The computer referred to here includes desktop or notebook personal computers, rack-mounted server computers, and the like. Furthermore, the computer also includes smartphones, mobile phones, PHS (Personal Handyphone System) and other mobile communication terminals, as well as PDAs (Personal Digital Assistants). The functions of the information processing device 10 may also be implemented on a cloud server.

[0082] An example of a computer that executes the above program (generation program) will be described using Figure 20. As shown in Figure 20, a computer 1000 includes, for example, a memory 1010, a CPU 1020, a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. These components are connected by a bus 1080.

[0083] The memory 1010 includes a read-only memory (ROM) 1011 and a random access memory (RAM) 1012. The ROM 1011 stores a boot program such as a basic input / output system (BIOS). The hard disk drive interface 1030 is connected to a hard disk drive 1090. The disk drive interface 1040 is connected to a disk drive 1041. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1041. The serial port interface 1050 is connected to a mouse 1110 and a keyboard 1120, for example. The video adapter 1060 is connected to a display 1130, for example.

[0084] 20, the hard disk drive 1090 stores, for example, an OS 1091, an application program 1092, a program module 1093, and program data 1094. The storage unit 13 described in the above embodiment is provided in, for example, the hard disk drive 1090 or the memory 1010.

[0085] Then, the CPU 1020 reads out the program module 1093 and the program data 1094 stored in the hard disk drive 1090 into the RAM 1012 as necessary, and executes the above-mentioned procedures.

[0086] The program module 1093 and program data 1094 relating to the above-described generation program are not limited to being stored in the hard disk drive 1090, but may be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1041. Alternatively, the program module 1093 and program data 1094 relating to the above-described program may be stored in another computer connected via a network such as a LAN or a WAN (Wide Area Network), and read by the CPU 1020 via the network interface 1070.

[0087] REFERENCE SIGNS LIST 10 Information processing device 11 Communication control unit 13 Storage unit 13A Questionnaire DB 13B Privacy policy DB 15 Control unit 15A Questionnaire presentation unit 15B Response collection unit 15C Score calculation unit 15D Privacy policy generation unit 15E Correction unit 15F Update detection unit 30 User terminal

Claims

1. An information processing device characterized by having: a collection unit that collects responses to a questionnaire set based on a combination of a first item regarding the type of personal information that is the subject of a privacy policy and a second item regarding the handling of the personal information; and a generation unit that generates a privacy policy corresponding to the responses to the questionnaire.

2. The information processing device described in claim 1, characterized in that the collection unit collects responses to a questionnaire that accepts the selection of whether to agree or disagree to the use of the personal information for each combination of a first item regarding the information type and a second item regarding the handling.

3. The information processing device described in claim 1, characterized in that the collection unit collects responses to a questionnaire including questions evaluating privacy concerns regarding a combination of a first item regarding the information type and a second item regarding the handling, and the generation unit generates a privacy policy corresponding to a type classified by the responses to the questionnaire from among multiple types.

4. The information processing device described in claim 3, further comprising a calculation unit that calculates a score that evaluates the degree of privacy concerns based on the answers included in the questionnaire, and wherein the generation unit generates a privacy policy corresponding to a type among the multiple types that is classified by the score calculated by the calculation unit.

5. The information processing device according to claim 3, wherein the collection unit collects responses to a questionnaire that includes questions that comply with the IUIPC (Internet Users' Information Privacy Concerns) model.

6. The information processing device according to claim 1, further comprising a modification unit that modifies the privacy policy based on a change operation made to the privacy policy generated by the generation unit.

7. A generation method executed by an information processing device, comprising: a collection step of collecting responses to a questionnaire set based on a combination of a first item regarding the type of personal information that is the subject of the privacy policy and a second item regarding the handling of the personal information; and a generation step of generating a privacy policy corresponding to the responses to the questionnaire.

8. A generation program for causing a computer to execute a collection step of collecting responses to a questionnaire set based on a combination of a first item regarding the type of personal information subject to the privacy policy and a second item regarding the handling of the personal information, and a generation step of generating a privacy policy corresponding to the responses to the questionnaire.

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