Information sharing method, device and system

Abstract

The present application provides an information sharing method, device and system, wherein the information sharing method includes: receiving an information sharing request sent by a target user node; sending the information sharing request to a data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information; receiving the privacy calculation result sent by the data party node; processing the privacy calculation result according to a preset statistical rule, and sending the processing result to the target user node. The present application can improve the reliability and comprehensiveness of shared information, and at the same time will not leak the original data of each data party, and can ensure the security of the data.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an information sharing method, device and system. Background Art

[0002] With the development of computer technology, many organizations have the need to build IT systems; each complex IT system is composed of many kinds of hardware and software, and a software is also composed of a development framework, middleware and various components. The construction process inevitably involves the selection of hardware and software. For the sake of ease of description, it is collectively referred to as "component product selection."

[0003] Currently, the main way to select component products is to collect and research public information and consult relevant manufacturers or consulting companies. However, public information cannot obtain details on the current technology production and use. Manufacturers often deliberately promote the technical architecture advantages that are beneficial to them and conceal disadvantages for commercial purposes. At the same time, it is difficult to obtain component product information used in production by organizations that have built microservice platforms, including: version number, usage time, number of failures, and purchase price.

[0004] For organizations, whether for security or business reasons, they will not disclose information about the component product selection of IT systems; and this information is obviously very valuable for an organization that is preparing to build an IT system with a microservice architecture. Summary of the invention

[0005] In response to the problems in the prior art, the present application proposes an information sharing method, device and system, which can improve the reliability and comprehensiveness of shared information while not leaking the original data of each data party and can ensure the security of the data.

[0006] In order to solve the above technical problems, this application provides the following technical solutions:

[0007] In a first aspect, the present application provides an information sharing method, comprising:

[0008] Receive an information sharing request sent by a target user node;

[0009] Sending the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information;

[0010] Receive the privacy calculation results sent by the data party node;

[0011] The privacy calculation result is processed according to preset statistical rules, and the processing result is sent to the target user node.

[0012] Furthermore, obtaining the component product information of the data party node and performing privacy calculation on the component product information according to the information sharing request includes:

[0013] According to the information sharing request, obtaining component product information of the data party node;

[0014] A secure multi-party computing protocol and the component product information are used to perform privacy computing.

[0015] Furthermore, sending the information sharing request to the data party node so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information includes:

[0016] The information sharing request is sent to each data party node respectively, so that each data party node decomposes the component product information of the data party node into multiple sub-component product information according to the information sharing request and the secure multi-party computing protocol; the sub-component product information is randomly exchanged between the data party nodes with the same component product name and version number, and the sum of the sub-component product information of each data party node after the exchange is obtained as the privacy calculation result of the data party node.

[0017] Furthermore, the processing of the privacy calculation result according to a preset statistical rule and sending the processing result to the target user node includes:

[0018] Receive privacy calculation results sent by each data party node;

[0019] The privacy calculation results corresponding to the data cube nodes with the same component product name and version number are summed to obtain the processing result;

[0020] The processing result is sent to the target user node.

[0021] Further, sending the processing result to the target user node includes:

[0022] encrypting the processing result;

[0023] The encrypted processing result is sent to the target user node, so that the target user node decrypts the encrypted processing result.

[0024] In a second aspect, the present application provides an information sharing device, comprising:

[0025] A request receiving module, used for receiving an information sharing request sent by a target user node;

[0026] A privacy computing module, used to send the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy computing based on the component product information;

[0027] A receiving module, used to receive the privacy calculation results sent by the data party node;

[0028] A processing module is used to process the privacy calculation result according to a preset statistical rule and send the processing result to the target user node.

[0029] Furthermore, the processing module includes:

[0030] An encryption unit, used for encrypting the processing result;

[0031] The decryption unit is used to send the encrypted processing result to the target user node so that the target user node decrypts the encrypted processing result.

[0032] In a third aspect, the present application provides an information sharing system, comprising:

[0033] User node, multiple data party nodes and the information sharing device;

[0034] The user node and the data party node are communicatively connected via the information sharing device, and each data party node is communicatively connected with each other.

[0035] In a fourth aspect, the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the information sharing method when executing the program.

[0036] In a fifth aspect, the present application provides a computer-readable storage medium having computer instructions stored thereon, which implement the information sharing method when the instructions are executed.

[0037] It can be seen from the above technical solution that the present application provides an information sharing method, device and system. Among them, the method includes: receiving an information sharing request sent by a target user node; sending the information sharing request to a data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information; receiving the privacy calculation result sent by the data party node; processing the privacy calculation result according to a preset statistical rule, and sending the processing result to the target user node, which can improve the reliability and comprehensiveness of the shared information, and at the same time will not leak the original data of each data party, and can ensure the security of the data; specifically, the existing technology relies on offline research on the production situation of each manufacturer, which takes a lot of time and manpower costs, while this solution can obtain the desired information through simple online operations, which can greatly save time and manpower costs; at the same time, this solution can protect sensitive or confidential information in production by adopting a privacy calculation method, and give full play to the greater value of data; through information security sharing, it is conducive to the development of the industry, thereby improving the industry's business and service level. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 is a flowchart of the information sharing method in an embodiment of the present application;

[0040] Figure 2 It is a flowchart of step 021 to step 023 of the information sharing method in an embodiment of the present application;

[0041] Figure 3 It is a schematic diagram of the interaction scenario between the user node, the coordinator node and the data node in the specific application example of the present application;

[0042] Figure 4 It is a structural diagram of an information sharing device in an embodiment of the present application;

[0043] Figure 5 It is a logical schematic diagram between the user node, the coordinator node and the data node in the embodiment of the present application;

[0044] Figure 6 This is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0046] In order to facilitate the understanding of this solution, the technical contents related to this solution are explained below.

[0047] Privacy computing is a technology that ensures data is “available but invisible” and is applied in various data security fields. Privacy computing includes multi-party secure computing and federated learning.

[0048] Secure Multi-Party Computation (MPC): refers to multiple participants holding their own private data, jointly executing a calculation logic (such as maximum value calculation) and obtaining the calculation result. However, in the process, each participating party will not leak the calculation of their own data; MPC calculation can be done through the design of the protocol without relying on a trusted third party. The characteristics of this technology are: MPC can ensure the security of the data of all parties while jointly using the data of all parties to achieve a specific effect, thereby giving full play to the value of the data.

[0049] Federated Learning (FL) technology: It is an encrypted distributed machine learning framework that aims to protect information security and terminal data security during data exchange and prevent data leakage; it ensures that efficient machine learning is carried out among multiple participants or multiple settlement nodes under the premise of legality and compliance, and realizes joint modeling to improve the effectiveness of AI models.

[0050] Homomorphic encryption: It is a special encryption algorithm that allows calculations to be performed directly on the encrypted ciphertext, and the calculation results are exactly the same as the plaintext calculation results after decryption. It is widely used in privacy protection.

[0051] Microservices: is a software development technique - a variation of the service-oriented architecture (SOA) architectural style that structures applications as a set of loosely coupled services. In a microservices architecture, services are fine-grained and protocols are lightweight.

[0052] Microservices (or microservices architecture): is a cloud-native architectural approach in which a single application consists of many smaller components or services that are loosely coupled and can be deployed independently. These services typically: 1) have their own stack, including database and data model; 2) communicate with each other through a combination of REST APIs, event streams, and message brokers; 3) are organized by business capabilities, with the lines separating services often called bounded contexts. Although much of the discussion about microservices revolves around architectural definitions and characteristics, their value can be more generally understood through fairly simple business and organizational benefits: 1) code can be updated more easily; 2) teams can use different stacks for different components;

[0053] 3) Components can be scaled independently of each other, reducing the waste and cost of having to scale the entire application because a single function might face excessive load.

[0054] With the continuous development of big data technology in recent years, the value of data assets has been increasingly valued by a large number of enterprises and institutions. The issue of data privacy leakage has also become a hot topic of concern. Data leakage incidents occur frequently, causing huge losses to the enterprises involved, including public services, finance, energy, medical care, Internet, education, transportation and manufacturing industries. Therefore, multiple laws and regulations related to data security at the national and regional levels are being gradually formulated and improved. However, due to the requirements of these laws and regulations, the challenge of data use is that data islands are constantly forming, and a large amount of data is dormant and cannot play its value. Many personal data and corporate data are restricted by legal and regulatory requirements and cannot be directly used for plaintext transactions; for some enterprises, many data are the core assets of the enterprise, and they are unwilling to share or conduct plaintext transactions; even if consensus on data transactions can be reached between enterprises, it is technically difficult to ensure the authentication of systems and identities across enterprises. At the same time, these plaintext data face the risk of being leaked and abused after the transaction, and the data value cannot be preserved.

[0055] At the same time, many organizations currently have the need to build IT systems, such as building big data platforms for data analysis, building artificial intelligence platforms for algorithm training, building blockchain platforms for information storage and traceability, etc., or the original IT systems need to be iteratively updated with the development of technology to adopt new technical architectures or development frameworks, such as transforming from a centralized architecture to a distributed architecture or a microservice architecture.

[0056] The quality of component products can be evaluated from many dimensions, among which the actual use of component products in production is one of the most important reference information for selection. For example, if an organization hopes to transform the technical architecture of the IT system from a centralized architecture to a microservice architecture, then it will inevitably involve the selection of a microservice framework, such as the Dubbo framework, SpringCloud framework, other commercial microservice frameworks, or self-developed ones. Assuming that the Spring Cloud framework is selected, the various business function components in the framework also involve selection work, such as whether the service registration and discovery function uses Nacos, Eureka, or self-developed. In the process of component selection, we hope to obtain first-hand information and evaluation materials from real users. However, when we need to conduct technical research on these companies, we often encounter great obstacles in management, process, and law, making it difficult to obtain specific details and expand the coverage of the research.

[0057] Based on this, in order to improve the reliability and comprehensiveness of shared information, and at the same time not to leak the original data of each data party and ensure the security of the data, the embodiment of the present application provides an information sharing device, which can be a server or a client device, and the client device can include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), a vehicle-mounted device, and a smart wearable device, etc. Among them, the smart wearable device can include smart glasses, smart watches, and smart bracelets, etc.

[0058] In practical applications, the information sharing part can be performed on the server side as described above, or all operations can be completed in the client device. The specific selection can be based on the processing capability of the client device and the limitations of the user's usage scenario. This application does not limit this. If all operations are completed in the client device, the client device may also include a processor.

[0059] The client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission with the server. The server may include a server on the task scheduling center side, and other implementation scenarios may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, or a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0060] The server and the client device may communicate using any suitable network protocol, including network protocols that have not yet been developed on the date of filing this application. The network protocol may include, for example, TCP / IP protocol, UDP / IP protocol, HTTP protocol, HTTPS protocol, etc. Of course, the network protocol may also include, for example, RPC protocol (Remote Procedure Call Protocol) and REST protocol (Representational State Transfer) used on top of the above protocols.

[0061] The details are described through the following embodiments.

[0062] In order to improve the reliability and comprehensiveness of shared information and prevent the original data of each data party from being leaked, thereby ensuring the security of the data, this embodiment provides an information sharing method in which the execution subject is an information sharing device, and the information sharing device includes but is not limited to a server, such as Figure 1 As shown, the method specifically includes the following contents:

[0063] Step 100: Receive an information sharing request sent by a target user node.

[0064] Specifically, the information sharing request may include a system category of a component product; the target user node includes but is not limited to a server.

[0065] Step 200: Send the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information.

[0066] Specifically, after receiving the information sharing request, the data party node can query the database; the database of each data party node can store multiple component product records of the data party node, and the record containing the system category in the information sharing request will be used as the component product information; the data party node includes but is not limited to the server. The component product information can include: classification items and indicator items; the classification items can include: system category, component product name and version number, etc.; the indicator items can include: usage time, failure frequency and price, etc.; the number of the data party nodes can be multiple; the component product information in each data party node can be stored locally in the data party node in the following format:

[0067] [System category, component product name, version number, usage time, number of failures, price, whether there are security vulnerabilities, difficulty of operation and maintenance, etc.]

[0068] Step 300: Receive the privacy calculation result sent by the data party node.

[0069] Step 400: Process the privacy calculation result according to preset statistical rules, and send the processing result to the target user node.

[0070] Specifically, the target user node can select the next component product based on the processing results; the preset statistical rules can include: the correspondence between the data type of the indicator item and the processing method of the privacy calculation result; for example, if the data type of the indicator item is numerical, such as "usage time", then the maximum value, minimum value, average value, median value and standard deviation of the "usage time" in the privacy calculation results sent by multiple data party nodes with the same component product name and version number can be obtained; if the indicator item type is non-numerical, such as "whether there is a security vulnerability", the proportion of the "value" can be counted, and the value with the most overlap can be taken. In one example, the processing result sent to the target user node can be shown in Table 1.

[0071] Table 1

[0072]

[0073] Assuming that there are 10 data cube nodes in the alliance, and 5 of them use MySQL as a database component of the big data platform, the usage of MySQL accounts for 50%.

[0074] In order to further improve the degree of automation of component product selection, in one example, after obtaining the processing result, the target component product name and version number can be determined based on the processing result and a preset component product selection model, and the processing result, target component product name and version number are sent to the target user node; the preset component product selection model can be pre-trained by applying a decision tree model.

[0075] In order to further illustrate this solution, this application provides an application example of an information sharing method, which is specifically described as follows:

[0076] Step 101: The user initiates an information sharing request to the coordinator node to query the component product information corresponding to a certain system (such as a big data platform) used by each data node in the alliance.

[0077] Step 102: The coordinator node sends the information sharing request to the data party node, and coordinates each data party node to respond to the information sharing request using a secure multi-party computing protocol (such as PIR / PPSA secure multi-party statistics, etc.), that is, the data party node completes the computing task specified by the protocol locally.

[0078] Specifically, the secure multi-party computing protocol can be stored in each data party node.

[0079] Step 103: After completing the local computing task according to the secure multi-party computing protocol, each data node returns the intermediate computing result calculated by itself to the coordinating node.

[0080] Among them, the computing task may include multiple rounds of computing, and the corresponding computing process is completed according to the protocol design; the secure multi-party computing protocol can ensure that the coordinating node cannot infer the data information owned by the data party through the intermediate results.

[0081] Step 104: The coordinator node processes the intermediate calculation results returned by each data party according to the secure multi-party computing protocol, and encrypts the final calculation results and returns them to the user.

[0082] In order to further improve the security of component product information and ensure that the component product information of each data party node is not leaked, in one embodiment of the present application, the step 200 of obtaining the component product information of the data party node according to the information sharing request and performing privacy calculation based on the component product information includes:

[0083] Step 201: Obtain component product information of the data party node according to the information sharing request.

[0084] Step 202: Apply the secure multi-party computing protocol and the component product information to perform privacy computing.

[0085] Specifically, the secure multi-party computing protocol may include: the correspondence between the data type and processing method of the indicator item, which can be pre-configured in each data party node according to actual needs; for example, if the data type of the indicator item is a numeric type, the processing method may be to split the indicator item in the component product information into multiple fragments and send them to different data party nodes; each data party node uses the sum of the remaining fragments and the received fragments as the privacy calculation result of the data party node; if the data type of the indicator item is a numeric type, the processing method may also be to encrypt the component product information and use the encrypted component product information as the privacy calculation result, so that the coordinator node processes the encrypted component product information, and the coordinator node cannot obtain the component product information and can only determine the processing result.

[0086] In order to further improve the reliability of privacy computing and thus improve the security of information sharing, see Figure 2 In one embodiment of the present application, step 200 includes:

[0087] Step 211: Send the information sharing request to each data cube node respectively, so that each data cube node decomposes the component product information of the data cube node into multiple sub-component product information according to the information sharing request and the secure multi-party computing protocol; the data cube nodes with the same product name and version number randomly exchange the sub-component product information and obtain the sum of the local sub-component product information of each data cube node after the exchange as the privacy calculation result of the data cube node.

[0088] For example, the component product information is that the number of failures x is decomposed into x1, x2 and x3, and x=x1+x2+x3.

[0089] Specifically, the secure multi-party computing protocol may also include the component product name and version number of each data party node; the data party node may determine other data party nodes that have the same component product name and version number as the data party node based on the local secure multi-party computing protocol and randomly send or exchange sub-component product information to the other data party nodes.

[0090] In order to further improve the reliability of the processing results, and thus improve the security and accuracy of information sharing, step 400 includes:

[0091] Step 401: Receive the privacy calculation results sent by each data party node.

[0092] Step 402: sum up the privacy calculation results corresponding to each data cube node with the same product name and version number to obtain the processing result.

[0093] For example, the privacy calculation results corresponding to each data cube node whose product name is Redis and whose version number is 2.1.1 can be summed up to obtain the total number of failures of the Redis database with version number 2.1.1; the privacy calculation results corresponding to each data cube node whose product name is Mysql and whose version number is 6.5.2 can be summed up to obtain the total number of failures of the Mysql database with version number 6.5.2.

[0094] Step 403: Send the processing result to the target user node.

[0095] In order to further illustrate this solution, this application also provides a specific application example of the information sharing method, such as Figure 3 The specific description is as follows:

[0096] Step 1: The coordinator node receives an information sharing request sent by the user node, where the information sharing request includes: a system category and a public key of the user node, where the system category is "database".

[0097] Step 2: The coordinator node sends the information sharing request to each data party node. Assume that there are only two data party nodes in the alliance, namely data party node A and data party node B (the case of multiple data parties can be inferred by analogy).

[0098] Specifically, data party nodes A and B obtain component product information from their respective databases according to the system category, and the component product information includes: the product name, version number and indicator items of their own database; the product name, version number and indicator items of the database of data party node A are: redis, 1.0.0 and number of failures x; the product name, version number and indicator items of the database of data party node B are: redis, 1.0.0 and number of failures y.

[0099] Using the secure multi-party computing protocol, data nodes A and B perform privacy computing on the number of redis failures. The privacy computing process specifically includes:

[0100] 1) Data node A randomly decomposes x into the sum of multiple numbers. Assume that x is decomposed into x1, x2 and x3, and x = x1 + x2 + x3. The other party does not know how many numbers x is decomposed into. Similarly, data node B also randomly decomposes y, assuming that y = y1 + y2 + y3 + y4.

[0101] Specifically, the secure multi-party computing protocol may include: the correspondence between the data type of the indicator item and the processing method; in this specific application example, the data type of the indicator item "number of failures" corresponding to the data party nodes A and B is "numeric"; therefore, the processing method is that the data party node disassembles its own indicator item to obtain multiple numbers, and then exchanges them between the data party nodes.

[0102] 2) Data node A randomly selects i decomposed numbers and sends them to B through the coordinator. Assume that A sends x1 to B; similarly, data node B randomly selects j decomposed numbers and sends them to A through the coordinator. Assume that B sends y2 and y4 to A.

[0103] 3) Data party node A locally sums the received y2 and y4 with the remaining x2 and x3 to calculate Ma=x2+x3+y2+y4; similarly, data party node B locally sums Mb=y1+y3+x1.

[0104] Step 3: The data node sends the intermediate calculation results to the coordinating node; that is, the data node A and the data node B send the intermediate calculation results Ma and Mb to the coordinating node; the coordinating node processes the intermediate calculation results according to preset statistical rules.

[0105] Specifically, the preset statistical rules may include: the correspondence between the data type of the indicator item and the processing method of the intermediate calculation result; in this application example, the indicator item "failure times" corresponding to the data cube nodes A and B is "numeric type", and the processing method corresponding to the intermediate calculation result is determined to be averaged: N = (Ma + Mb) / 2; according to the preset statistical rules, it is determined that the coordinator node needs to coordinate the number of failures of each data cube node for the database with the same product name, and calculate the average value. Before and after the calculation process, each data cube node does not expose the number of failures of its own redis.

[0106] Step 4: The coordinator node encrypts N with the user node’s public key and returns it to the user node; the user node decrypts it with the private key to obtain the result.

[0107] In order to avoid leakage of processing results and further improve the security of data transmission, in one embodiment of the present application, sending the processing results to the target user node in step 400 includes:

[0108] Step 401: Encrypt the processing result.

[0109] Step 402: Send the encrypted processing result to the target user node, so that the target user node decrypts the encrypted processing result.

[0110] Specifically, the information sharing request may also include the public key of the target user node; the public key of the target user node may be used to encrypt the processing result; after the encrypted processing result is sent to the target user node, the target user node uses a private key to decrypt the encrypted processing result.

[0111] From the software level, in order to improve the reliability and comprehensiveness of shared information, while not leaking the original data of each data party and ensuring the security of the data, this application provides an embodiment of an information sharing device for implementing all or part of the content of the information sharing method, see Figure 4 , the information sharing device specifically includes the following contents:

[0112] A request receiving module 01 is used to receive an information sharing request sent by a target user node;

[0113] The privacy computing module 02 is used to send the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy computing based on the component product information;

[0114] Receiving module 03, used to receive the privacy calculation result sent by the data party node;

[0115] The processing module 04 is used to process the privacy calculation result according to a preset statistical rule and send the processing result to the target user node.

[0116] In one embodiment of the present application, the processing module includes:

[0117] An encryption unit, used for encrypting the processing result;

[0118] The decryption unit is used to send the encrypted processing result to the target user node so that the target user node decrypts the encrypted processing result.

[0119] The information sharing device embodiment provided in this specification can be specifically used to execute the processing flow of the above-mentioned information sharing method embodiment. Its functions will not be described in detail here, and reference can be made to the detailed description of the above-mentioned information sharing method embodiment.

[0120] In order to improve the reliability and comprehensiveness of shared information, while not leaking the original data of each data party and ensuring the security of the data, the present application provides an embodiment of an information sharing system, such as Figure 5 As shown, in this embodiment, the information sharing system includes:

[0121] A user node, a plurality of data-party nodes and the information sharing device; wherein the user node and the data-party node are connected in communication via the information sharing device, and each data-party node is connected in communication with each other (not in Figure 5 (displayed in the figure).

[0122] Specifically, the information sharing device is the coordinator node; the user node, multiple data party nodes (such as data party node A to data party node C) and the information sharing device can all be servers; the user node can represent the statistical information demander of the production and usage of the component product; the data party node can represent the institution that owns the statistical information of the production and usage of the component product, and participates in the calculation according to the protocol; the information sharing device, namely the coordinator node, can transfer information between the user node and the data party node; coordinate multiple parties to participate in the calculation during the privacy computing process; the data party node and the coordinator node are in the same secure network; the user node and the data party node exchange information through the coordinator node.

[0123] To further illustrate this solution, this application provides an application example of an information sharing system. In this application example, the information sharing system is an IT system component product information sharing alliance in production, including: user nodes, data party nodes and coordination party nodes; the alliance manager is responsible for coordinating members to jointly build a privacy computing platform, namely, the component product information sharing alliance. In this application example, the information sharing system is specifically described as follows:

[0124] 1) Data node, providing relevant component product information and computing services of its own IT production system. Alliance members jointly discuss the indicators for evaluating component product information and the storage format. Data node stores component product information according to alliance rules, and the storage format should at least include "classification items" and "indicator items".

[0125] In one example, component product information can be classified according to "system category", "component product name", and "version number", and "duration of use", "failure frequency", "price", "whether there are security vulnerabilities" and "difficulty of operation and maintenance" can be used as evaluation indicators. The sharing alliance can formulate specific indicators based on the consensus of members. The indicator items can cover the evaluation of product component functions, performance, security, ease of use, operation and maintenance, etc. In addition, this information can only be stored locally on the data party node and cannot be obtained by other members of the alliance or the privacy computing platform.

[0126] 2) Users enter the "system category" x they want to query through the privacy computing platform, and they can obtain statistical information y on the production and usage of all corresponding component products under this system category, that is, y=f(x). Users pay the data provider who provides the information. The statistical rule f is jointly formulated by the alliance members, and the present invention does not limit the specific statistical rules or calculation rules. Statistics can be performed according to different rules based on the data type of the indicator item. For example, if the indicator item is "numeric", the maximum value, minimum value, average value, median value, standard deviation, etc. can be counted; if the indicator item is "non-numeric", the proportion of "values" can be counted, the value with the most overlap can be taken, etc.

[0127] In one example, y can be a statistical table about the use of component products in production, counting how many members of all alliance members are using a certain version of a component product in a certain category of production system, that is, the usage percentage; the maximum, minimum, and average usage time of users; the maximum, minimum, and average number of failures; the highest, lowest, and average purchase price, etc. The format of each record in the statistical table is as follows:

[0128] [Component product name, version number, usage percentage, maximum usage time, minimum usage time, average usage time, maximum number of failures, minimum number of failures, average number of failures, maximum price, minimum price, average price, …]

[0129] 3) The coordinating node is responsible for coordinating the data party nodes to jointly calculate statistical information. The calculation process adopts privacy computing related technologies (such as multi-party secure computing and federated learning, etc.) to ensure that the production and use information of the component products of the data party nodes will not be known by other members and the coordinating node. For example, the homomorphic encryption technology can be used to encrypt the data of all parties, and the ciphertext can be used for calculation. The ciphertext result is then delivered to the user, and the user decrypts it to obtain it; or, multi-party secure computing can be used to coordinate each data party node to only perform a certain step of the calculation, provide the encrypted intermediate result to the coordinating node, and then the coordinating node calculates the final result and feeds back to the user.

[0130] From the above description, it can be seen that the information sharing method, device and system provided by the present application can improve the reliability and comprehensiveness of shared information, and at the same time will not leak the original data of each data party, and can ensure the security of the data; specifically, the existing technology relies on offline research on the production situation of each manufacturer, which takes a lot of time and manpower costs, while the present solution can obtain the desired information through simple online operations, which can greatly save time and manpower costs; at the same time, the present solution can protect sensitive or confidential information in production by adopting privacy computing methods, thereby maximizing the value of data; through the safe sharing of information, it will help the development of the industry, thereby improving the industry's business and service levels.

[0131] From the hardware level, in order to improve the reliability and comprehensiveness of shared information, while not leaking the original data of each data party and ensuring the security of the data, the present application provides an embodiment of an electronic device for implementing all or part of the content of the information sharing method. The electronic device specifically includes the following content:

[0132] A processor, a memory, a communications interface and a bus; wherein the processor, the memory and the communications interface communicate with each other through the bus; the communications interface is used to realize information transmission between the information sharing device and related devices such as user terminals; the electronic device can be a desktop computer, a tablet computer and a mobile terminal, etc., but the present embodiment is not limited thereto. In the present embodiment, the electronic device can be implemented with reference to the embodiments for realizing the information sharing method and the embodiments for realizing the information sharing device, and the contents thereof are incorporated herein, and the repeated parts are not repeated.

[0133] Figure 6 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Figure 6 As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Figure 6is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0134] In one or more embodiments of the present application, the information sharing function may be integrated into the central processing unit 9100. The central processing unit 9100 may be configured to perform the following control:

[0135] Step 100: Receive an information sharing request sent by a target user node.

[0136] Step 200: Send the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information.

[0137] Step 300: Receive the privacy calculation result sent by the data party node.

[0138] Step 400: Process the privacy calculation result according to preset statistical rules, and send the processing result to the target user node.

[0139] It can be seen from the above description that the electronic device provided by the embodiments of the present application can improve the reliability and comprehensiveness of shared information while not leaking the original data of each data party, thereby ensuring data security.

[0140] In another embodiment, the information sharing device may be configured separately from the central processing unit 9100. For example, the information sharing device may be configured as a chip connected to the central processing unit 9100, and the information sharing function may be implemented under the control of the central processing unit.

[0141] like Figure 6 As shown, the electronic device 9600 may also include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Figure 6 In addition, the electronic device 9600 may also include Figure 6 For components not shown, reference may be made to the prior art.

[0142] like Figure 6 As shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0143] The memory 9140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 9100 may execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0144] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display may be, for example, an LCD display, but is not limited thereto.

[0145] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 9600 through the central processor 9100.

[0146] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0147] The communication module 9110 is a transmitter / receiver 9110 that sends and receives signals via an antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0148] Based on different communication technologies, multiple communication modules 9110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module, etc. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, thereby realizing a common telecommunication function. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processor 9100, so that recording can be performed on the local machine through the microphone 9132, and the sound stored on the local machine can be played through the speaker 9131.

[0149] It can be seen from the above description that the electronic device provided by the embodiments of the present application can improve the reliability and comprehensiveness of shared information while not leaking the original data of each data party, thereby ensuring data security.

[0150] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the information sharing method in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps of the information sharing method in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0151] Step 100: Receive an information sharing request sent by a target user node.

[0152] Step 200: Send the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information.

[0153] Step 300: Receive the privacy calculation result sent by the data party node.

[0154] Step 400: Process the privacy calculation result according to preset statistical rules, and send the processing result to the target user node.

[0155] It can be seen from the above description that the computer-readable storage medium provided in the embodiment of the present application can improve the reliability and comprehensiveness of shared information while not leaking the original data of each data party, thereby ensuring the security of the data.

[0156] In this application, each embodiment of the above method is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. For relevant parts, refer to the partial description of the method embodiment.

[0157] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0158] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0159] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0160] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0161] Specific embodiments are used in this application to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core idea of ​​this application. At the same time, for those skilled in the art, according to the idea of ​​this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on this application.

Claims

1. An information sharing method, characterized in that: include: Receive an information sharing request sent by a target user node; Sending the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information; Receiving the privacy calculation result sent by the data party node; Processing the privacy calculation result according to a preset statistical rule, and sending the processing result to the target user node; The sending of the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information, includes: The information sharing request is sent to each data party node respectively, so that each data party node decomposes the component product information of the data party node into multiple sub-component product information according to the information sharing request and the secure multi-party computing protocol; the sub-component product information is randomly exchanged between the data party nodes with the same component product name and version number, and the sum of the sub-component product information of each data party node after the exchange is obtained as the privacy calculation result of the data party node.

2. The information sharing method according to claim 1, characterized in that: The obtaining, according to the information sharing request, component product information of the data party node and performing privacy calculation on the component product information includes: According to the information sharing request, obtaining component product information of the data party node; A secure multi-party computing protocol and the component product information are used to perform privacy computing.

3. The information sharing method according to claim 1, characterized in that: The processing of the privacy calculation result according to a preset statistical rule and sending the processing result to the target user node includes: Receive privacy calculation results sent by each data party node; The privacy calculation results corresponding to the data cube nodes with the same component product name and version number are summed to obtain the processing result; The processing result is sent to the target user node.

4. The information sharing method according to claim 1, characterized in that: The sending the processing result to the target user node includes: encrypting the processing result; The encrypted processing result is sent to the target user node, so that the target user node decrypts the encrypted processing result.

5. An information sharing device, characterized in that: include: A request receiving module, used for receiving an information sharing request sent by a target user node; A privacy computing module, used to send the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy computing based on the component product information; A receiving module, used to receive the privacy calculation results sent by the data party node; A processing module, used to process the privacy calculation result according to a preset statistical rule, and send the processing result to the target user node; The sending of the information sharing request to the data party node, so that the data party node obtains the component product information of the data party node according to the information sharing request and performs privacy calculation based on the component product information, includes: The information sharing request is sent to each data party node respectively, so that each data party node decomposes the component product information of the data party node into multiple sub-component product information according to the information sharing request and the secure multi-party computing protocol; the sub-component product information is randomly exchanged between the data party nodes with the same component product name and version number, and the sum of the sub-component product information of each data party node after the exchange is obtained as the privacy calculation result of the data party node.

6. The information sharing device according to claim 5, characterized in that: The processing module comprises: An encryption unit, used for encrypting the processing result; The decryption unit is used to send the encrypted processing result to the target user node so that the target user node decrypts the encrypted processing result.

7. An information sharing system, characterized in that: include: User nodes, data party nodes and the information sharing device as claimed in claim 5 or 6; The user node and the data party node are communicatively connected via the information sharing device, and each data party node is communicatively connected with each other.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the information sharing method according to any one of claims 1 to 4 is implemented.

9. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instructions are executed, the information sharing method according to any one of claims 1 to 4 is implemented.

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