Information processing apparatus, method, program, and system

Abstract

To support the formulation of IT rules.SOLUTION: A program according to one aspect of the present disclosure causes a computer to function as: means for acquiring target organization information which is information relating to a usage pattern of IT (Information Technology) infrastructure in a target organization or attributes of the target organization; means for determining recommended rules which are recommended IT rules for the target organization based on knowledge of rules for the usage of the IT infrastructure by the organization and the acquired target organization information; and means for outputting the determined recommended rules.SELECTED DRAWING: Figure 7

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, a method, a program, and a system. [Background technology]

[0002] For example, organizations such as companies may use various IT (Information Technology) assets (e.g., IT devices and software) or IT services (e.g., cloud services such as SaaS (Software as a Service)) in their business operations. From the perspective of security and governance, it is desirable for organizations to establish rules (hereinafter referred to as "IT rules") for their use of at least one of their IT assets or IT services (hereinafter referred to as "IT infrastructure"). However, it is not easy for small and medium-sized organizations, in particular, to independently formulate IT rules that are suited to their specific circumstances.

[0003] Patent Document 1 discloses a technical idea intended to efficiently construct a security policy, which is a method for designing and implementing information security. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-056176 Summary of the Invention [Problem to be solved by the invention]

[0005] The technical idea of ​​Patent Document 1 may be useful for establishing security policies. However, because security policies and IT rules are different concepts, it is not easy to apply the technical idea of ​​Patent Document 1 directly to the formulation of IT rules.

[0006] The purpose of this disclosure is to assist in the formulation of IT rules. [Means for solving the problem]

[0007] A program according to one embodiment of the present disclosure causes a computer to function as a means for acquiring target organization information, which is information relating to the usage of IT (Information Technology) infrastructure in a target organization or the attributes of the target organization; a means for determining recommended rules, which are IT rules recommended to the target organization based on knowledge regarding rules for the organization's use of IT infrastructure and the acquired target organization information; and a means for outputting the determined recommended rules. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration of an information processing system according to an embodiment of the present invention; [Figure 2] FIG. 2 is a block diagram showing the configuration of a client device according to the present embodiment. [Figure 3] FIG. 2 is a block diagram showing the configuration of a server according to the present embodiment. [Figure 4] FIG. 1 is an explanatory diagram of one aspect of the present embodiment. [Figure 5] FIG. 2 is a diagram illustrating a data structure of a logic database according to the present embodiment. [Figure 6] FIG. 2 is a diagram illustrating a data structure of a question database according to the present embodiment. [Figure 7] 10 is a flowchart of an IT rule recommendation process according to the present embodiment. [Figure 8] 10A and 10B are diagrams illustrating examples of screens displayed in the IT rule recommendation process of the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In the drawings for explaining the embodiment, the same components are generally designated by the same reference numerals, and repeated description thereof will be omitted.

[0010] (1) Information processing system configuration The configuration of the information processing system will now be described with reference to Fig. 1, which is a block diagram showing the configuration of the information processing system according to this embodiment.

[0011] As shown in FIG. 1, the information processing system 1 includes a client device 10 and a server 30. The client device 10 and the server 30 are connected via a network (for example, the Internet or an intranet) NW.

[0012] The client device 10 is an example of an information processing device. The client device 10 is, for example, a smartphone, a tablet terminal, or a personal computer. A user of the client device 10 is, for example, a person who is involved in formulating IT rules for an organization.

[0013] The server 30 is an example of an information processing device. The server 30 is, for example, a server computer. For example, the server 30 may manage a Mobile Device Management (MDM) service for an organization. In this case, the information processing system 1 corresponds to an MDM system that provides the MDM service to the organization. Alternatively, the server 30 may be configured to be able to cooperate with an external MDM system that provides the MDM service.

[0014] (1-1) Client device configuration The configuration of the client device will now be described with reference to Fig. 2, which is a block diagram showing the configuration of the client device of this embodiment.

[0015] 2, the client device 10 includes a storage device 11, a processor 12, an input / output interface 13, and a communication interface 14. The client device 10 is connected to a display 21.

[0016] The storage device 11 is configured to store programs and data, and is, for example, a combination of a read-only memory (ROM), a random access memory (RAM), and a storage (for example, a flash memory or a hard disk).

[0017] The programs include, for example, the following programs: OS (Operating System) programs Applications that process information (e.g., web browsers)

[0018] The data includes, for example, the following data: Databases referenced in information processing Data obtained by performing information processing (i.e., the results of performing information processing)

[0019] The processor 12 is a computer that implements the functions of the client device 10 by running a program stored in the storage device 11. The processor 12 is, for example, at least one of the following: ·CPU(Central Processing Unit) ·GPU(Graphic Processing Unit) ·ASIC(Application Specific Integrated Circuit) ·FPGA(Field Programmable Gate Array)

[0020] The input / output interface 13 is configured to acquire information (for example, a user's instruction) from an input device connected to the client device 10, and to output information (for example, an image) to an output device connected to the client device 10.

[0021] The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof. The output device is, for example, a display 21, a speaker, or a combination thereof.

[0022] The communication interface 14 is configured to control communications between the client device 10 and an external device (eg, the server 30).

[0023] The display 21 is configured to display an image (a still image or a moving image). The display 21 is, for example, a liquid crystal display or an organic EL display.

[0024] (1-2) Server configuration The configuration of the server will now be described with reference to Fig. 3, which is a block diagram showing the configuration of the server according to this embodiment.

[0025] As shown in FIG. 3, the server 30 includes a storage device 31, a processor 32, an input / output interface 33, and a communication interface .

[0026] The storage device 31 is configured to store programs and data, and is, for example, a combination of ROM, RAM, and storage (for example, flash memory or a hard disk).

[0027] The programs include, for example, the following programs: OS programs Application programs that perform information processing

[0028] The data includes, for example, the following data: Databases referenced in information processing - Results of information processing

[0029] The processor 32 is a computer that implements the functions of the server 30 by running a program stored in the storage device 31. The processor 32 is, for example, at least one of the following: ·CPU GPU ASIC FPGA

[0030] The input / output interface 33 is configured to acquire information (for example, a user's instruction) from an input device connected to the server 30, and to output information (for example, an image) to an output device connected to the server 30.

[0031] The input device is, for example, a keyboard, a pointing device, a touch panel, or a combination thereof. The output device is, for example, a display.

[0032] The communication interface 34 is configured to control communications between the server 30 and an external device (eg, the client device 10).

[0033] (2) One aspect of the embodiment An example of this embodiment will now be described with reference to Fig. 4, which is an explanatory diagram of this example.

[0034] As shown in FIG. 4, the client device 10 receives input of target organization information from, for example, a user US 20. The user US 20 is typically a person, particularly an information system specialist, who belongs to an organization (hereinafter referred to as the "target organization") that requires the formulation of IT rules, but is not limited to this. For example, the user US 20 may be a person who does not belong to the target organization, such as a consultant who supports the target organization's IT operations. The organization is typically a company, but may also be a division that constitutes a company, a corporate group consisting of multiple companies, or an organization that does not fall under the category of a company, such as a public institution. The target organization information may include the usage pattern of the IT infrastructure in the target organization (the current usage pattern, requirements for the usage pattern (desired usage pattern), or a combination of these). The IT infrastructure may include IT assets. The IT assets may include, for example, IT devices (i.e., hardware such as PCs, smartphones, and tablet devices), software, middleware, data, or other information-related assets owned by the organization. The IT infrastructure may also include IT services instead of or in addition to IT assets. The IT services may include services using IT technology provided to the organization from outside, such as SaaS or other cloud services, or services related to other information. The target organization information may also include information related to the attributes of the target organization. The attributes may include, for example, industry, size (e.g., personnel scale, such as the number of members (employees)), sales, capital, listed status, or global expansion status. The client device 10 transmits the received target organization information to the server 30.

[0035] The server 30 acquires target organization information from at least one of the client device 10, another external device, or the storage device 31. The server 30 determines recommended rules based on knowledge about rules for the organization's use of IT infrastructure (i.e., IT rules) and the acquired target organization information. The knowledge can be inductively derived from examples of organizational information of various organizations and IT rules formulated for the organizations. The recommended rules are IT rules recommended for the target organization.

[0036] The server 30 outputs the determined recommended rules. For example, the server 30 transmits the recommended rules to the client device 10. The client device 10 may receive the recommended rules and display a screen based on the recommended rules on the display 21.

[0037] In this way, the server 30 of this embodiment determines IT rules recommended for the target organization based on knowledge and target organization information. This allows the user US 20 to obtain recommended rules that are IT rules suited to the actual situation of the target organization, and the user US 20 can use the recommended rules as they are or refine them to formulate IT rules for the target organization. This reduces the workload required to formulate IT rules.

[0038] (3) Database The databases of this embodiment will be described. The following databases are stored in the storage device 31.

[0039] (3-1) Logic Database The logic database of this embodiment will now be described with reference to Fig. 5, which shows the data structure of the logic database of this embodiment.

[0040] The logic database stores logic information. The logic information is information about the logic for determining rules according to how an organization uses its IT infrastructure. The logic information can correspond to knowledge built by aggregating and organizing examples of organizational information from various organizations and IT rules established for those organizations, or to commonly available information such as hints for establishing IT rules.

[0041] 5, the logic database includes a "logic ID" field, a "question ID" field, a "use mode" field, and a "rule" field. Each field is associated with another field.

[0042] The "Logic ID" field stores a logic ID, which uniquely identifies logic information.

[0043] The "Question ID" field stores a question ID. The question ID is information that uniquely identifies the question information. The question information is information related to a question to elicit from the user the usage status (current situation or requirements) of the IT infrastructure by the target organization.

[0044] The "usage mode" field stores usage mode information. The usage mode information is information about the usage mode in which a user is expected to answer a question identified by a corresponding question ID. Note that multiple different usage mode information may be associated with the same question ID. In FIG. 5, the usage mode information is expressed in natural language for convenience, but it may also be expressed in machine-readable language.

[0045] The "rule" field stores rule information. The rule information is information about rules that are suitable for the usage mode indicated by the corresponding usage mode information. In FIG. 5, the rule information is expressed in natural language for convenience, but it may also be expressed in machine-readable language.

[0046] The server 30 can determine recommendation rules without using a logic database, and therefore, in this embodiment, the logic database and the question database described below can be omitted.

[0047] (3-2) Question Database The question database of this embodiment will now be described with reference to Fig. 6, which is a diagram showing the data structure of the question database of this embodiment.

[0048] The question database stores question information, which, as described above, is information related to questions asked by users to elicit information about how the target organization uses its IT infrastructure.

[0049] 6, the question database includes a "Question ID" field and a "Question" field. Each field is associated with the other.

[0050] The "Question ID" field stores a question ID. The question ID is information that uniquely identifies question information.

[0051] The "Question" field stores question information. The question information may be designed to elicit the current state or requirements of the target organization's usage regarding at least one of the following themes, for example: -Personal use by members of the organization Access to organizational resources Access to inappropriate content Appropriate usage behavior Use of third-party software Password Policy Anti-virus policy Firewall settings Mobile device settings · Anti-phishing measures Using a VPN for remote work Devices used for remote work ·Communication security for remote work ·Security in a remote work environment · Software or middleware installation Software or middleware updates and patches License management for software, middleware, or IT services Prohibition on use of software, middleware, or IT services · BYOD (Bring Your Own Device) permission BYOD security requirements BYOD data management BYOD device types

[0052] Note that the server 30 may store question information instead of question IDs in the logic database, in which case the question database can be omitted in this embodiment.

[0053] (4) Information processing The information processing of this embodiment will be described.

[0054] (4-1) IT rule recommended processing The IT rule recommendation process of this embodiment will be described below. Fig. 7 is a flowchart of the IT rule recommendation process of this embodiment. Fig. 8 is a diagram showing an example of a screen displayed in the IT rule recommendation process of this embodiment.

[0055] As shown in FIG. 7, the server 30 acquires the target organization information (S130). Specifically, the server 30 acquires the target organization information from the client device 10 or another external device, or the storage device 31.

[0056] As a first example of acquiring target organization information (S130), the client device 10 accepts input of target organization information from a user and transmits the input result to the server 30. For example, the server 30 may present questions to the user via the client device 10 to elicit usage patterns of the IT infrastructure in the target organization, and the client device 10 may accept input of answers to the questions (i.e., current usage patterns or requests) from the user. For example, the client device 10 may display the screen of FIG. 8 on the display 21 and accept input of answers to each question from the user. The questions may be presented based on question information registered in a question database (FIG. 6).

[0057] The usage of the IT infrastructure in the target organization may include, for example, the current situation or requirements regarding at least one of the following: Number of IT device users in the target organization - Whether BYOD is available in the target organization Personal information handling policy of the target organization Budget for the use of IT infrastructure in the target organization

[0058] As a second example of acquiring target organization information (S130), the server 30 acquires target organization information accumulated in an MDM system that provides MDM services to the target organization. As a third example of acquiring target organization information (S130), the server 30 acquires target organization information (for example, information related to attributes) from public information related to the target organization. A fourth example of the acquisition of target organization information (S130) is a combination of multiple of the first to third examples.

[0059] After step S130, the server 30 determines the recommended rules (S131). Specifically, server 30 determines recommended rules based on the target organization information acquired in step S130 and knowledge related to rules for use of IT infrastructure by the organization. The knowledge may include knowledge based on information accumulated in an MDM service managed by server 30 or an MDM service with which server 30 can cooperate (hereinafter referred to as "MDM-related knowledge"). The knowledge may also include knowledge based on general information related to rules for use of IT infrastructure by the organization (for example, information describing the relationship between the characteristics of the organization and IT rules suitable for the organization).

[0060] MDM knowledge reflects the relationship between organizational information about an organization using an MDM service (e.g., the way the organization uses its IT infrastructure or organizational attribute information) and the organization's IT rules (e.g., the organization's IT infrastructure management system). The way the organization uses its IT infrastructure may include the way the organization uses MDM services. The organization's IT infrastructure management system may include the values ​​adopted by the organization for items that can be set in the MDM service. In MDM knowledge, information that can identify individual organizations using MDM services (e.g., the organization's name, location, etc.) is generally anonymized (e.g., masked).

[0061] Knowledge can be embedded in, for example, a table, a trained model, or a large-scale language model. That is, knowledge can be expressed as relationships between items that make up a table, or can be trained using a trained model or a large-scale language model. In the training data, information that can identify individual organizations using the MDM service (e.g., organization name, location, etc.) is generally anonymized (e.g., masked).

[0062] The recommended rules may include provisions regarding at least one of the following: -Scope of use of IT devices in the target organization Security settings in the target organization Remote work rules in the target organization Software available for use in the target organization

[0063] As a first example of determining recommended rules (S131), the server 30 uses knowledge about MDM. The server 30 identifies organizations (hereinafter referred to as "similar organizations") that are similar to the target organization with respect to any element of the target organization information acquired in step S130. For example, the server 30 may identify organizations that are similar to the target organization in terms of how the organizations use MDM services or their size. The server 30 references knowledge about MDM to acquire information about the IT infrastructure management systems of similar companies. The server 30 then determines recommended rules based on the IT infrastructure management systems of similar companies.

[0064] As a second example of determining a recommended rule (S131), the server 30 uses knowledge embedded in a table. This table associates, for example, characteristics of organizational information of an organization with IT rules suitable for that organization. The logic database in FIG. 6 is an example of such a table. The server 30 extracts information from the table that is associated with any element of the target organizational information acquired in step S130. The server 30 determines a recommended rule based on the extracted information.

[0065] As a third example of determining recommended rules (S131), the server 30 uses knowledge embedded in a trained model. This trained model is configured by machine learning to estimate IT rules recommended for an organization based on organizational information about the organization (i.e., the usage pattern of the IT infrastructure in the organization or the attributes of the organization). As training data, for example, a combination of model input based on the organizational information of the organization and training data based on IT rules adopted by the organization can be used. The server 30 determines recommended rules by providing the trained model with model input based on the target organization information acquired in step S130.

[0066] As a fourth example of determining recommended rules (S131), the server 30 uses knowledge embedded in a large-scale language model. This large-scale language model has undergone additional learning (fine-tuning) using the same learning data as the trained model described above. The server 30 determines recommended rules by providing the large-scale language model with a prompt including the target organization information acquired in step S130 and an instruction to output IT rules recommended to the target organization.

[0067] The fifth example of determining the recommended rule (S131) ​​is a combination of multiple of the first to fourth examples.

[0068] After step S131, the server 30 outputs the recommended rules (S132). Specifically, the server 30 outputs the recommended rule determined in step S131. As an example, the server 30 presents the recommended rule to the user via the client device 10. For example, the server 30 transmits the recommended rule to the client device 10. The client device 10 receives the recommended rule and displays a screen based on the recommended rule on the display 21.

[0069] After outputting the recommended rule (S132), the client device 10 accepts the user's approval or disapproval of the recommended rule as a whole or for each clause included in the rule. The client device 10 may output the rule approved by the user as a document file.

[0070] If the user of the client device 10 approves the recommended rules output in step S132, the server 30 may execute device configuration (S133). Specifically, the server 30 extracts clauses related to device setting values ​​recommended for IT devices used in the target organization from the recommended rules output in step S132. The server 30 sets the device setting values ​​defined in the extracted clauses in the IT devices used in the target organization. For example, the server 30 sets the device setting values ​​for the IT devices of the target organization registered in the MDM service by using the functions of the MDM service (via an API (Application Programming Interface) as necessary).

[0071] If the user of the client device 10 approves some clauses of the recommended rule, the server 30 may perform device configuration (S133) for the approved clauses and omit device configuration (S133) for the other clauses. The server 30 may also accept edits to the recommended rule output in step S132 from the user of the client device 10. In this case, the server 30 may perform device configuration (S133) based on the edited results of the recommended rule. Edits to the recommended rule may include changing or deleting clauses included in the recommended rule, adding clauses not included in the recommended rule, or a combination thereof. In other words, device configuration (S133) may be a step of conditionally setting device setting values ​​recommended for IT devices used in the target organization based on clauses related to the device setting values.

[0072] (5) Summary As described above, the server 30 of this embodiment acquires target organization information, which is information about the usage of IT infrastructure in a target organization or the attributes of the target organization. The server 30 determines recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for the organization's use of IT infrastructure and the acquired target organization information, and outputs the recommended rules. This allows the user to obtain recommended rules, which are IT rules that are appropriate for the target organization's actual situation, and the user can use the recommended rules as is or improve them to formulate IT rules for the target organization. In other words, the workload required for formulating IT rules can be reduced.

[0073] The knowledge may include knowledge based on information accumulated in the mobile device management service, which allows determining appropriate recommendation rules based on the usage history of the mobile device management service.

[0074] The knowledge based on information accumulated in the mobile device management service may include information on how the organization that uses the mobile device management service uses the mobile device management service and information on the organization's IT infrastructure management system. The server 30 may identify similar organizations that are similar to the target organization in terms of how they use the mobile device management service and determine recommended rules based on the IT infrastructure management systems of the similar organizations. This makes it possible to determine appropriate recommended rules based on the IT infrastructure management systems actually adopted by organizations that are similar to the target organization in terms of how they use the mobile device management service.

[0075] The knowledge based on information accumulated in the mobile device management service may include information on the size of organizations using the mobile device management service and information on the IT infrastructure management systems of those organizations. The server 30 may identify similar organizations that are similar in size to the target organization and determine recommended rules based on the IT infrastructure management systems of those similar organizations. This makes it possible to determine appropriate recommended rules based on the IT infrastructure management systems actually adopted by organizations similar in size to the target organization.

[0076] Knowledge may include knowledge based on general information about rules for the use of IT infrastructure by organizations, which can complement other knowledge, for example knowledge about MDM, to determine recommended rules for broader provisions.

[0077] The knowledge may be embedded in a table. The server 30 may extract information associated with the target organization information from the table and determine recommendation rules based on the extracted information. This allows the determination logic of recommendation rules for elements of the target organization information to be predefined, making it possible to stably provide high-quality recommendation rules within the defined range.

[0078] The knowledge may be embedded in the trained model. The server 30 may determine the recommendation rule by providing the trained model with model input based on the target organization information. This makes it possible to determine a recommendation rule that is estimated to be statistically valid without having to define the decision logic of the recommendation rule for each element of the target organization information.

[0079] The trained model may be configured by machine learning for estimating IT rules recommended to an organization based on the usage of the IT infrastructure in the organization or the attributes of the organization, thereby making it possible to determine recommended rules that are statistically estimated to be suitable for the usage of the IT infrastructure in the organization or the attributes of the organization.

[0080] The knowledge may be embedded in a large-scale language model. The server 30 may determine the recommended rules by providing the large-scale language model with prompts including target organization information and instructions for outputting IT rules recommended to the target organization. This makes it possible to determine recommended rules that are estimated to be statistically valid without having to define the decision logic for the recommended rules for each element of the target organization information.

[0081] The usage of the IT infrastructure in the target organization may include the current situation or requirements regarding at least one of the number of IT device users in the target organization, whether BYOD is permitted, the privacy policy, or the budget, thereby allowing the user to obtain recommended rules according to the details of the usage of the IT infrastructure in the target organization.

[0082] The recommended rules may include at least one of the range of use of IT devices in the target organization, security settings, remote work rules, and available software, thereby allowing the user to obtain recommended rules regarding the details of the target organization's use of IT infrastructure.

[0083] The recommended rules may include device setting values ​​recommended for IT devices in the target organization. The server 30 may conditionally set the device setting values ​​in the IT devices in the target organization. This eliminates or reduces the user's work of applying the device setting values ​​defined in the recommended rules to the IT devices actually used in the target organization. In other words, it is possible to quickly start implementing the IT rules and reduce the workload associated with preparing for implementation.

[0084] (6) Other variations The storage device 11 may be connected to the client device 10 via a network NW. The display 21 may be integrated with the client device 10. The storage device 31 may be connected to the server 30 via the network NW.

[0085] In the above description, examples have been given in which steps in each process are executed in a specific order, but the execution order of each step is not limited to the described example as long as there is no dependency between the steps. Furthermore, a process described as being performed by one device may be executed by another device, and a process described as being performed by the interaction of multiple devices may be executed by a single device. For example, each step of the above information processing may be executed by either the client device 10 or the server 30.

[0086] (7) Supplementary Notes The matters explained in the embodiment and the modified examples are additionally noted below.

[0087] (Appendix 1) A computer (30), A means for acquiring target organization information (S130), which is information relating to the usage of IT (Information Technology) infrastructure in the target organization or the attributes of the target organization; A means for determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information (S131); A means for outputting the determined recommended rules (S132); A program that functions as a

[0088] (Appendix 2) the knowledge includes knowledge based on information stored in a mobile device management service; The program described in Appendix 1.

[0089] (Appendix 3) The knowledge based on information accumulated in the mobile device management service includes information on how the organization that uses the mobile device management service uses the mobile device management service and information on the management system of IT infrastructure in the organization; the means for determining the recommended rule identifies similar organizations that are similar to the target organization in terms of how the mobile device management service is used, and determines the recommended rule based on the management system of IT infrastructure in the similar organizations; The program described in Appendix 2.

[0090] (Appendix 4) the knowledge based on information accumulated in the mobile device management service includes information on the size of an organization that uses the mobile device management service and information on the management system of IT infrastructure in the organization; the means for determining the recommended rules identifies similar organizations that are similar to the target organization in terms of size, and determines the recommended rules based on the IT infrastructure management systems of the similar organizations; The program described in Appendix 2.

[0091] (Appendix 5) The knowledge includes knowledge based on general information about rules for the use of IT infrastructure by organizations; The program described in Appendix 1.

[0092] (Appendix 6) The knowledge is embedded in a table; the means for determining the recommended rule extracts information associated with the target organization information from the table, and determines the recommended rule based on the extracted information. The program described in Appendix 1.

[0093] (Appendix 7) The knowledge is embedded in a trained model; the means for determining the recommended rule determines the recommended rule by providing a model input based on the target organization information to the trained model. The program described in Appendix 1.

[0094] (Appendix 8) The trained model is configured by machine learning to estimate IT rules recommended for an organization based on the usage of the organization's IT infrastructure or the attributes of the organization. 7. The program described in Appendix 7.

[0095] (Appendix 9) The knowledge is embedded in a large-scale language model; the means for determining the recommended rule determines the recommended rule by providing the large-scale language model with a prompt including the target organization information and an instruction for outputting an IT rule recommended to the target organization. The program described in Appendix 1.

[0096] (Appendix 10) The usage of the IT infrastructure in the target organization includes the current situation or requirements regarding at least one of the number of users of IT devices in the target organization, whether BYOD (Bring Your Own Device) is permitted, personal information handling policy, or budget; The program described in Appendix 1.

[0097] (Appendix 11) The recommended rules include at least one of the scope of use of IT devices in the target organization, security settings, remote work rules, or available software; The program described in Appendix 1.

[0098] (Appendix 12) the recommendation rules include device setting values ​​recommended for IT devices used in the target organization; The computer is further caused to function as a means (S133) for conditionally setting the device setting value in an IT device used in the target organization. A program according to any one of Supplementary Note 1 to Supplementary Note 11.

[0099] (Appendix 13) A computer (30) A step (S130) of acquiring target organization information, which is information on the usage of IT (Information Technology) infrastructure in the target organization or the attributes of the target organization; A step (S131) ​​of determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information; a step (S132) of outputting the determined recommended rules; How to do it.

[0100] (Appendix 14) A means for acquiring target organization information (S130), which is information relating to the usage of IT (Information Technology) infrastructure in the target organization or the attributes of the target organization; A means for determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information (S131); A means for outputting the determined recommended rule (S132); An information processing device (30) comprising:

[0101] (Appendix 15) A system (1) including a plurality of information processing devices (10, 30), A means for acquiring target organization information (S130), which is information relating to the usage of IT (Information Technology) infrastructure in the target organization or the attributes of the target organization; A means for determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information (S131); A means for outputting the determined recommended rule (S132); A system comprising:

[0102] Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited to the above-described embodiments. Furthermore, the above-described embodiments can be improved or modified in various ways without departing from the spirit of the present invention. Furthermore, the above-described embodiments and modifications can be combined. [Explanation of symbols]

[0103] 1: Information processing system 10: Client device 11:Storage device 12: Processor 13: Input / output interface 14: Communication interface 21: Display 30: Server 31:Storage device 32: Processor 33: Input / output interface 34: Communication interface

Claims

1. Computer, A means for acquiring target organization information, which is information regarding the usage of IT (Information Technology) infrastructure in the target organization or the attributes of the target organization; a means for determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information; means for outputting the determined recommended rules; A program that functions as a

2. the knowledge includes knowledge based on information stored in a mobile device management service; The program according to claim 1.

3. the knowledge based on information accumulated in the mobile device management service includes information on how the organization that uses the mobile device management service uses the mobile device management service and information on the management system of the IT infrastructure in the organization; the means for determining the recommended rule identifies similar organizations that are similar to the target organization in terms of how they use the mobile device management service, and determines the recommended rule based on the management system of IT infrastructure in the similar organizations. The program according to claim 2.

4. the knowledge based on information accumulated in the mobile device management service includes information on the size of an organization that uses the mobile device management service and information on the management system of IT infrastructure in the organization; the means for determining the recommended rules identifies similar organizations that are similar to the target organization in terms of size, and determines the recommended rules based on the management systems of IT infrastructures in the similar organizations; The program according to claim 2.

5. The knowledge includes knowledge based on general information regarding rules for the use of IT infrastructure by organizations. The program according to claim 1.

6. The knowledge is embedded in a table; the means for determining the recommended rule extracts information associated with the target organization information from the table, and determines the recommended rule based on the extracted information. The program according to claim 1.

7. The knowledge is embedded in a trained model; the means for determining the recommended rule determines the recommended rule by providing a model input based on the target organization information to the trained model. The program according to claim 1.

8. The trained model is configured by machine learning for estimating IT rules recommended for an organization based on the usage pattern of the organization's IT infrastructure or the attributes of the organization. The program according to claim 7.

9. The knowledge is embedded in a large-scale language model; the means for determining the recommended rule determines the recommended rule by providing the large-scale language model with a prompt including the target organization information and an instruction for outputting an IT rule recommended to the target organization. The program according to claim 1.

10. The usage of the IT infrastructure in the target organization includes the current situation or requirements regarding at least one of the number of users of IT devices in the target organization, whether BYOD (Bring Your Own Device) is available, personal information handling policy, or budget; The program according to claim 1.

11. The recommended rules include at least one of a range of use of IT devices in the target organization, security settings, remote work rules, and available software. The program according to claim 1.

12. the recommendation rules include device setting values ​​recommended for IT devices used in the target organization; The computer is further configured to function as a means for conditionally setting the device setting value in an IT device used in the target organization.

12. The program according to claim 1.

13. The computer acquiring target organization information, which is information relating to the usage of IT (Information Technology) infrastructure in a target organization or the attributes of the target organization; determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information; outputting the determined recommended rules; How to do it.

14. A means for acquiring target organization information, which is information on the usage of IT (Information Technology) infrastructure in a target organization or the attributes of the target organization; a means for determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information; means for outputting the determined recommended rules; An information processing device comprising:

15. A system including a plurality of information processing devices, A means for acquiring target organization information, which is information on the usage of IT (Information Technology) infrastructure in a target organization or the attributes of the target organization; a means for determining recommended rules, which are IT rules recommended to the target organization, based on knowledge about rules for use of IT infrastructure by the organization and the acquired target organization information; means for outputting the determined recommended rules; A system comprising:

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