CN115495774A

CN115495774A - Risk data query method, system, trusted unit and server

Info

Publication number: CN115495774A
Application number: CN202211055274.1A
Authority: CN
Inventors: 陈远; 郭倩婷; 王辛民; 李书博; 孙善禄; 杨仁慧; 杨文玉; 钱锋
Original assignee: Ant Blockchain Technology Shanghai Co Ltd
Current assignee: Ant Blockchain Technology Shanghai Co Ltd
Priority date: 2022-08-31
Filing date: 2022-08-31
Publication date: 2022-12-20

Abstract

A risk data query method, a system, a trusted unit and a server, the method comprises the following steps: the first mechanism equipment sends the ciphertext query data to the server; the server provides the ciphertext query data to the trusted unit; the trusted unit decrypts the ciphertext query data to obtain a first user identifier of the first user, and processes the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user; sending a second user identification of the first user to a server; the server sends a query request to the blockchain, and the query request is used for querying whether a risk user list stored in the blockchain comprises a second user identifier of the first user; the block chain inquires according to the inquiry request and returns the inquiry result to the server; and when determining that the risk user list does not comprise the second user identification of the first user according to the query result, the server returns first information to the first mechanism equipment, wherein the first information is used for indicating that the first user is not a risk user.

Description

Risk data query method, system, trusted unit and server

Technical Field

The embodiment of the specification belongs to the technical field of computers, and particularly relates to a risk data query method, a risk data query system, a trusted unit and a server.

Background

Currently, regulatory authorities often require institutions involved in major transactions to fulfill their obligations against illegal funds transfers. Namely, transaction data of large-amount transactions and suspicious transactions are analyzed and reported. However, information isolation between organizations forms an information island, and organizations have difficulty identifying suspicious users in the event of insufficient information. How to protect the private data of a user while sharing risk information by a plurality of organizations is a problem to be solved in the current anti-illegal fund transfer scheme.

Disclosure of Invention

The invention aims to provide a risk data query scheme, which is used for querying risk data by combining a server, a trusted unit and a block chain, so that the risk data query efficiency is improved.

In a first aspect of the present specification, a risk data query method is provided, including:

the method comprises the steps that first mechanism equipment sends ciphertext query data to a server, the ciphertext query data are obtained by encrypting the query data, the query data comprise a first user identification of a first user to be queried, and the first mechanism equipment belongs to a first mechanism;

the server provides the ciphertext query data to a trusted unit;

the trusted unit decrypts the ciphertext query data to obtain a first user identifier of the first user, and processes the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user; sending a second user identification of the first user to the server;

the server sends a query request to the blockchain, wherein the query request is used for querying whether a second user identifier of the first user is included in a risk user list stored in the blockchain, and the risk user list is generated based on a plurality of risk data from a plurality of organizations and comprises the second user identifiers of a plurality of risk users;

the block chain inquires whether the risk user list comprises a second user identifier of the first user or not according to the inquiry request, and returns the inquiry result to the server;

and when determining that the risk user list does not comprise the second user identification of the first user according to the query result, the server returns first information to the first mechanism device, wherein the first information is used for indicating that the first user is not a risk user.

A second aspect of the present specification provides a risk data query method, including:

the method comprises the steps that first mechanism equipment sends ciphertext query data to a trusted unit, the ciphertext query data are obtained by encrypting the query data, the query data comprise a first user identification of a first user to be queried, and the first mechanism equipment belongs to a first mechanism;

the trusted unit decrypts the ciphertext query data to obtain a first user identifier of the first user, and processes the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user; sending a query request to the blockchain for querying whether a second user identifier of the first user is included in a risk user list stored in the blockchain, wherein the risk user list is generated based on a plurality of risk data from a plurality of organizations and comprises the second user identifiers of a plurality of risk users;

the block chain inquires whether the risk user list comprises a second user identifier of the first user according to the inquiry request, and returns the inquiry result to the trusted unit;

and when determining that the second user identifier of the first user is not included in the risk user list according to the query result, the trusted unit returns first information to the first mechanism device, wherein the first information is used for indicating that the first user is not a risk user.

A third aspect of the present specification provides a risk data query method, performed by a server, the method including:

receiving ciphertext query data from first mechanism equipment, wherein the ciphertext query data are obtained by encrypting the query data, the query data comprise a first user identifier of a first user to be queried, and the first mechanism equipment belongs to a first mechanism;

providing the ciphertext query data to a trusted unit;

receiving a second user identification of the first user from the trusted unit, wherein the second user identification of the first user is obtained by processing the first user identification of the first user through a preset algorithm;

sending a query request to the blockchain for querying whether a second user identifier of the first user is included in a risk user list stored in the blockchain, wherein the risk user list is generated based on a plurality of risk data from a plurality of organizations and comprises the second user identifiers of a plurality of risk users;

receiving query results from the blockchain;

and when determining that the second user identification of the first user is not included in the risk user list according to the query result, returning first information to the first mechanism device, wherein the first information is used for indicating that the first user is not a risk user.

A fourth aspect of the present specification provides a risk data query method, executed by a trusted unit, including:

decrypting the ciphertext query data to obtain a first user identifier of the first user, and processing the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user;

receiving query results from the blockchain;

A fifth aspect of the present specification provides a risk data query system, comprising a first organization device, a server, a blockchain system and a trusted unit for private data processing,

the first mechanism equipment is used for sending ciphertext query data to the server, the ciphertext query data are obtained by encrypting the query data, the query data comprise a first user identifier of a first user to be queried, and the first mechanism equipment belongs to a first mechanism;

the server is used for providing the ciphertext query data to a trusted unit;

the trusted unit is used for decrypting the ciphertext query data, acquiring a first user identifier of the first user, and processing the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user; sending a second user identification of the first user to the server;

the server is further configured to send a query request to the blockchain, for querying whether a second user identifier of the first user is included in a risk user list stored in the blockchain, the risk user list being generated based on a plurality of risk data from a plurality of organizations and including the second user identifiers of a plurality of risk users;

the block chain system is used for inquiring whether the risk user list comprises a second user identifier of the first user according to the inquiry request and returning the inquiry result to the server;

the server is further configured to return first information to the first mechanism device when it is determined that the second user identifier of the first user is not included in the risk user list according to the query result, where the first information is used to indicate that the first user is not a risk user.

A sixth aspect of the present specification provides a server comprising:

the system comprises a receiving unit, a first organization device and a second organization device, wherein the receiving unit is used for receiving ciphertext query data from the first organization device, the ciphertext query data are obtained by encrypting the query data, the query data comprise a first user identification of a first user to be queried, and the first organization device belongs to the first organization;

a providing unit configured to provide the ciphertext query data to a trusted unit;

the receiving unit is further configured to: receiving a second user identification of the first user from the trusted unit, wherein the second user identification of the first user is obtained by processing the first user identification of the first user through a preset algorithm;

a sending unit, configured to send an inquiry request to the blockchain, where the inquiry request is used to inquire whether a second user identifier of the first user is included in a risk user list stored in the blockchain, and the risk user list is generated based on multiple risk data from multiple organizations and includes the second user identifiers of multiple risk users;

the receiving unit is further configured to receive a query result from the blockchain;

and a returning unit, configured to, when it is determined that the second user identifier of the first user is not included in the risk user list according to the query result, return first information to the first mechanism device, where the first information is used to indicate that the first user is not a risk user.

A seventh aspect of the specification provides a trusted unit comprising:

the decryption unit is used for decrypting the ciphertext query data to obtain a first user identifier of the first user, and processing the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user;

and a returning unit, configured to, when it is determined that the risk user list does not include the second user identifier of the first user according to the query result, return first information to the first mechanism device, where the first information is used to indicate that the first user is not a risk user.

An eighth aspect of the present specification provides a computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method of the second or third aspect.

A ninth aspect of the present specification provides a computing device comprising a memory having stored therein executable code and a processor which, when executing the executable code, implements the method of the second or third aspect.

In the embodiment of the description, by combining the trusted unit and the block chain to execute the risk data query method, the mechanism device performs desensitization, encryption and other processing on information of a user to be queried to obtain a user identifier and sends the user identifier to the trusted unit, and the trusted unit further performs processing on the user identifier by using a preset algorithm to obtain the desensitization user identifier, so as to query whether a risk user list stored in the block chain includes the desensitization user identifier, thereby protecting user privacy and improving query speed in a real-time query scene.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments described in the present disclosure, and it is obvious for a person skilled in the art to obtain other drawings based on these drawings without inventive labor.

FIG. 1 is a schematic diagram of a system in an embodiment of the present description;

fig. 2 is a flowchart of a method for generating a ciphertext risk data file on the mechanism device side in an embodiment of the present specification;

FIG. 3 is a flow chart of a method for verifying identity of an organization by a server in an embodiment of the present description;

FIG. 4 is a flow chart of a risk data sharing method in one embodiment of the present description;

FIG. 5 is a schematic diagram of a process of generating a risk union file in an embodiment of the present specification;

FIG. 6 is a flowchart of a method for generating a risk query file ciphertext at an organization device side in an embodiment of the present disclosure;

FIG. 7 is a flow chart of a risk data query method in an embodiment of the present description;

FIG. 8 is a flow chart of a method for querying risk data in an embodiment of the present description;

FIG. 9 is a flow chart of a risk data query method in an embodiment of the present description;

FIG. 10 is a flow chart of a risk data query method in an embodiment of the present description;

FIG. 11 is an architecture diagram of a server in an embodiment of the present disclosure;

fig. 12 is an architecture diagram of a trusted unit in an embodiment of the present specification.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

Data sharing is often a requirement for organizations to handle traffic. Often, a single organization cannot acquire enough information to handle the service, and thus, a need exists to acquire information from other organizations. For example, among the requirements of anti-illegal fund transfer compliance for performing, many countries require that each financial institution provide an anti-illegal fund transfer audit result. Currently, many countries, the central authorities, and many large financial institutions have attempts to utilize blockchains in the area of anti-illegal funds transfer to improve efficiency and accuracy and meet regulatory requirements. Meanwhile, as a resource, the mobility and the availability of data are the basis of the development of many data applications and industries, but privacy protection in the data exchange and sharing process is always a great challenge in the development of the industries. The above-described illegal fund transfer will be described as an example.

Common illegal fund transfer approaches widely relate to various fields such as banks, insurance, securities, real estate and the like. Most anti-illegal funds transfer jobs involve three core issues:

1. a customer identity recognition system. When the anti-illegal fund transfer obligation body establishes a business relationship with a client or conducts a transaction with the client, the identity of the client is verified and recorded according to the real and effective identity certificate, and the identity information of the client is timely updated during the service relationship.

2. Large and Suspicious Transaction Report (STR) systems. Illegal fund flow generally has the characteristics of huge amount, abnormal transaction and the like, so a large amount and suspicious transaction reporting system is stipulated by law, and a financial institution is required to report abnormal transactions with the amount reaching a certain standard and without legal purposes to an anti-illegal fund transfer administrative department in time so as to be used as a clue for pursuing illegal criminal behaviors.

3. The customer identity data and the transaction record storage system stores the customer identity data and the transaction record, means that a financial institution adopts necessary measures to store the customer identity data and the transaction information for a certain period of time according to law, and can provide evidence support for pursuing criminal behaviors.

The Customer identification system, also known as "Know Your Customer" (KYC), refers to obtaining Customer-related identification information, including knowing the Customer's identity when establishing a service with the Customer, knowing the purpose of the transaction, knowing the source and destination of the funds, and knowing the long business activities and financial transaction conditions of the Customer, and is the basis of anti-illegal fund transfer.

Different financial institutions are obligated to review suspicious transactions. However, the information of the transaction related to the same user and the information of the user, which are held between different financial institutions, are often different, so that the risk labels, which are indexed after the suspicious transaction analysis is performed on the same user by different financial institutions, may also be different, where the risk labels include, for example, a plurality of preset labels, and each label is used to indicate an illegal fund transfer risk level of the user, an illegal behavior type of the user, or other information related to the illegal fund transfer risk of the user. If a financial institution is to more accurately index a risk label to a user, a better way is to be able to obtain a risk label that another (or more) financial institution indexes the same user. Thus, a need has arisen to share risk labels of the same user among different financial institutions.

Taking the illegal fund transfer risk level of the client as an example, the illegal fund transfer risk levels indexed by different financial institutions after performing suspicious transaction analysis on the same user may also be different, for example, the illegal fund transfer risk indexed by the first institution to the user U1 is a high risk, and the illegal fund transfer risk indexed by the second institution to the same user U1 is a medium risk. If a financial institution is to more accurately index a user with an illegal funds-transfer risk level label, it is preferable to be able to obtain an illegal funds-transfer risk level label that another (or more) financial institution indexes the same user. Thus, a need has arisen to share the same user's illegal funds transfer risk level labels among different financial institutions.

Fig. 1 is a schematic diagram of a system in an embodiment of the present description. As shown in fig. 1, the institution devices 100, 200, and 300 may be computing devices such as institution a, institution B, and institution C, respectively, which may be any of financial, insurance, transaction, etc. institutions, for example. It will be appreciated that three facility devices are shown as an example and that in practice other numbers of multiple facility devices may be included. The client of the illegal fund transfer resisting platform is installed in the mechanism equipment, and each mechanism equipment can directly receive the information of the user, so that the client can complete certain processing work based on the information of the user, such as the examination of suspicious transactions, and the risk label of each user can be obtained.

Taking the risk label specifically as the illegal fund transfer risk level as an example, the organization a and the organization B can index the illegal fund transfer risk level to the user respectively based on the anti-illegal fund transfer auditing capability of the organization a and the organization B. Thus, the illegal funds transfer risk levels that institution a and institution B respectively index for user U1 may not be the same. For example, organization A indexes an illegal funds transfer risk level label for user U1 as [ high risk level ], and organization B indexes an illegal funds transfer risk level label for user U1 as [ medium risk level ]. In order to obtain a more accurate illegal funds transfer risk level, illegal funds transfer risk level labels of the same user may be shared among a plurality of institutions through an anti-illegal funds transfer server (hereinafter, simply referred to as server) 400. However, in this process of risk data sharing, a plurality of compliance requirements need to be satisfied. For example, an organization that provides risk data in risk data sharing may not know the organization that queries the data it provides, the organization that queries the risk data may not know which organization provided the risk data, and the server may not know which organization's data the organization queries, and the plaintext data that is queried. These compliance requirements increase the difficulty of sharing and querying the risk data.

The server 400 includes a Trusted unit, which may be any computing unit that can perform private data or confidential data processing and protect data from leakage, for example, the Trusted unit includes a Trusted Execution Environment (TEE), a computing device in a Trusted authority, and the like. An example of TEE40 as a trusted unit is shown in fig. 1, and TEE40 is described below as an example of a trusted unit. Each facility device may send the desensitized and encrypted ciphertext risk data to server 400, and server 400 stores the ciphertext risk data for each facility in a local or file storage server (not shown in fig. 1). TEE40 may receive an address storing risk data from server 400, obtain ciphertext risk data from the address, perform fusion processing on risk data of multiple organizations, and obtain a risk user list, where a user identifier in the risk user list is an identifier subjected to desensitization processing. In the embodiment of the present specification, the query of the user risk data may be performed based on the risk user list. The server 400 and the TEE40 may be connected to the blockchain 500, and perform the risk data query scheme in the embodiment of the present disclosure in conjunction with the blockchain 500. It is to be appreciated that although the trusted unit is shown in fig. 1 as being located inside the server 400, embodiments of the present description are not limited thereto, and the TEE may also be located in another computing device to which the server 400 may be connected by connecting with the computing device.

Fig. 2 is a flowchart of a method for generating a ciphertext risk data file on the mechanism device side in the embodiment of the present specification. The mechanism apparatus in fig. 2 may be any one of the plurality of mechanism apparatuses in fig. 1. The mechanism apparatus 100 is described below as an example.

As shown in fig. 2, first, in step S201, the agency device 100 reads the initial risk data file F1, and acquires user identification information and a risk label.

In the institution a corresponding to the institution apparatus 100, the institution administrator may periodically generate an initial risk data file F1 in the institution apparatus 100 according to the data analysis result in the institution a for sharing the risk data to other institutions. It is to be understood that, although the risk data and the following other risk information are carried in the form of a file, the embodiments of the present specification are not limited thereto, and for example, the risk data or the risk information may also be carried in the form of data or a table, which is not limited thereto. This file F1 includes identity information and an insurance label for the risky users in organization a. The identity information includes, for example, a name, a certificate number, and the like. The risk label is a label which indicates the risk degree and is negotiated by a plurality of organizations. For example, the risk label may include a risk label such as riskH, for example indicating high risk, riskM, for example indicating medium risk, riskL, for example indicating low risk. The risk label of a single user may also include multiple risk labels, such as risk1, riskH, where risk1 for example indicates a particular type of risk, and so on. Specifically, the file F1 may include a plurality of lines, each of which may be in the form of:

"name/certType/certNum/risk1, riskH", where name is the user's name, certType is the certificate type, certNum is the certificate number, and these three constitute the three elements of the user's identity information.

After the facility administrator generates the file F1 in the facility device 100, the file F1 is uploaded to the storage of the client. After monitoring the update of the file F1, the client may read the file F1 line by line, for example, so as to obtain the identity information and the risk label of each risk user.

In step S203, the agency device 100 determines whether a user ID corresponding to the identity information is stored locally.

In order to protect the privacy of the user, it is necessary to perform desensitization processing on the user identity information in the file F1, that is, the user identity information cannot be directly included in the shared file transmitted from the mechanism device 100. Therefore, each organization only needs to use the same user ID for the same user to replace the identity information of the user. Specifically, for the user identity information in one row in the file F1, the client in the facility device 100 first determines whether the user ID corresponding to the identity information is stored locally. For example, the client may determine whether the identity information and the corresponding user ID are included in a mapping table of a preset address in the hard disk. If not, the client may perform step S205, requesting the user ID of the user from the server 400.

In step S205, the agency device 100 requests the user ID of the user from the server 400.

Specifically, since the server 400 is also not fully trusted, the agency device 100 also needs to desensitize the three-factor information of the user when requesting the user ID from the server 400. Specifically, the agency device may calculate a hash value hash1= hash (name + certType + certNum) of the three-factor information, where "+" may indicate sequential concatenation of two items of data, and then the agency device 100 may transmit the hash value hash1 to the server 400 to request a user ID corresponding to the hash value.

In step S207, the server 400 returns the user ID of the user to the facility device 100.

After receiving hash1, the server 400 may calculate an ID corresponding to hash1 using a preset rule.

In one embodiment, to further enhance data security, the server 400 may perform a salt operation on hash1, for example, by calculating hash (hash 1+ salt), and using the obtained hash value as the user ID, where salt is a value generated by the server in advance. The user ID is obtained by adopting the salting operation on the hash1, so that a malicious party can be prevented from presuming the three-element information corresponding to the hash 1.

After determining the user ID, the server returns the user ID to the agency device 100. When other institutions request the user ID for the user from server 400, the server may calculate the user ID for the user based on the same rules and parameters, and may obtain the same user ID, and return the user ID to the institution device, so that different institutions use the same user ID for the same user in the risk data file they send to the server.

In step S209, the agency device 100 stores the user identification information and the user ID in association.

The agency device 100, after receiving the user ID from the server 400, stores the user identification information and the user ID in association, for example, in a persistent medium, so that they can be used for subsequent processing of the updated risk file. Specifically, the agency device may store the user identification information and the user ID in association in the mapping table.

In step S211, the facility device 100 writes the user ID and the risk label in the risk data file F2.

In the case where the agency device 100 determines in step S203 that the user ID corresponding to the identity information is stored locally (e.g., in the mapping table described above), step S211 may be directly performed. Alternatively, the mechanism apparatus 100 may perform step S211 after performing step S209.

The client in the facility device 100 may initialize the file F2 while starting reading the file F1, and after reading a line of the corresponding user ID in the file F1 line by line, record the user ID and the risk label of the user in the file F2 in a line corresponding to the line in the file F1. In this way, the client can generate the risk data file F2 corresponding to the file F1 after performing the above-described processing for each line in the file F1.

In one embodiment, after the client generates the file F2 as described above, the rows in the file F2 may be sorted in ascending order of the respective user IDs to facilitate the subsequent process of merging risk data files of multiple organizations.

In step S213, the client may also encrypt the file F2 using the public key of the TEE, thereby generating a ciphertext risk data file F3. By this, the TEE outside of the server 400 cannot acquire the risk value corresponding to each user ID, and user privacy is further protected. It will be appreciated that the encryption of file F2 using the TEE's public key is not limited thereto, for example, other asymmetric or symmetric keys may be negotiated between the TEE and the facility device for encrypting file F2.

The TEE is a trusted execution environment which is based on the safety extension of CPU hardware and is completely isolated from the outside. The industry is concerned with TEE solutions, and almost all mainstream chip and Software consortiums have their own TEE solutions, such as TPM (Trusted Platform Module) in Software, and Intel SGX (Software Guard Extensions) in hardware, ARM Trustzone, and AMD PSP (Platform Security Processor). The TEE can function as a hardware black box, and codes and data executed in the TEE cannot be peeped even in an operating system layer, and can be operated only through an interface predefined in the codes. In terms of efficiency, due to the black box nature of the TEE, plaintext data is operated on in the TEE, rather than the complex cryptographic operations in homomorphic encryption, and little loss in computational process efficiency occurs.

The Intel SGX (hereinafter referred to as SGX) technology is taken as an example. The block link points may create enclaves (enclosures or enclaves) as TEEs based on SGX technology. The server may allocate a partial area EPC (enclosure Page Cache, enclave Page Cache, or Enclave Page Cache) in the memory by using a processor instruction newly added to the CPU, so as to reside the above enclosure. The Memory area corresponding to the EPC is encrypted by a Memory Encryption Engine MEE (Memory Encryption Engine) inside the CPU, the content (code and data in the enclave) in the Memory area can be decrypted only in the CPU core, and a key for Encryption and decryption is generated and stored in the CPU only when the EPC is started. It can be seen that the security boundary of enclave only includes itself and CPU, and no matter privileged or non-privileged software can not access enclave, even an operating system administrator and VMM (Virtual Machine Monitor, or Hypervisor) can not affect the code and data in enclave, so that the enclave has extremely high security. And the data entering and exiting the TEE can be encrypted, so that the privacy of the data is guaranteed.

The TEE may prove to the user that it is authentic before it is used. The process of certifying itself as authentic may involve remote certification reporting. The remote attestation report results from a remote attestation process to the TEE. The remote attestation report may be generated by an authoritative authentication server verifying referral information generated by the TEE. The remote attestation report may be used to indicate that the TEE is trusted.

For example, the institution device 100 may first verify that the TEE is authentic before encrypting the file F2 using the TEE's public key. Specifically, the facility device 100 may initiate a challenge to the TEE and receive a remote attestation report back from the TEE. After obtaining the remote attestation report, the authority device 100 may verify the signature of the remote attestation report according to the public key of the authoritative certification server, and may confirm that the TEE is authentic if the verification is passed. Specifically, after receiving the verification request, the TEE generates authentication information based on its internal mechanism, and sends the authentication information and the hardware public key of the TEE to the agency device 100. The authentication information includes, for example, signature information, hardware information, software information, and the like of the TEE. Wherein the signature information is generated, for example, by a hardware key of the TEE; the hardware information includes, for example, indicators of various hardware, such as CPU host frequency, memory capacity, and the like; the software information includes a code hash value, a code name, a version, an operation log, etc. of each program. As known to those skilled in the art, a TEE may perform a "measurement" of the program running therein through memory hardware, such as obtaining a code hash value of the program, a hash value of the memory occupancy of the program at a particular execution point, etc., and include in the authentication information "measurement" information for the program, which is authentic because the "measurement" information is executed by the TEE's own entity (memory hardware) without involving any software, operating system, etc. The agency device 100, upon receiving the authentication information, may send the authentication information to a remote authentication server of the TEE, thereby receiving a remote attestation report for the TEE from the server. The remote attestation report includes, among other things, authentication of the TEE, and authentication of programs executing within the TEE. Thus, the agency device 100 may determine that the TEE is authentic based on the remote attestation report, and the results of the query by the TEE are authentic. At the same time, the agency device 100 may locally hold the TEE's hardware public key for subsequent verification of the TEE's signature. Wherein, a pair of public and private keys is stored in the TEE, and the private key is kept in the TEE properly. Content transmitted by the TEE may be signed with a private key stored within the TEE, thereby proving the result of execution by the TEE.

In embodiments of the present description, a digital identity may be created for each organization by way of the DIS in conjunction with the blockchain. The blockchain may provide a decentralized (or weakly centralized), non-tamperpble (or difficult to tamper) trusted distributed ledger and may provide a secure, stable, transparent, auditable, and efficient way to log transactions and data-information interactions. The blockchain network may include a plurality of nodes. Typically one or more nodes of a blockchain are attributed to a participant. In general, the more participants in the blockchain network, the more authoritative the participants are, and the higher the trustworthiness of the blockchain network is. A blockchain network formed by a plurality of participants is referred to herein as a blockchain platform. With the help of the blockchain platform, the identity of the organization can be verified.

To use the distributed digital identity services provided by the blockchain platform, an organization may register its own identity in the blockchain platform. For example, organization a may create a pair of public and private keys, the private key being stored securely, and may create a distributed digital identity (also known as Decentralized identifiers, DID). The DID may be created by institution a itself or may be requested by a Distributed Identity Service (DIS) system to create the DID. DIS is an identity management scheme based on a block chain, and can provide functions of creating, verifying, managing and the like of digital identities, thereby realizing standardized management and protection of entity data, ensuring the authenticity and efficiency of information transfer, and solving the problems of cross-organization identity authentication, data cooperation and the like. The DIS system may be connected to a blockchain platform. And a DID can be created for the organization A through the DIS system, the DID and the public key are sent to the block chain platform for storage, and the created DID is returned to the organization A. The public key may be included into a DIDdoc, which may be stored in a blockchain platform. The DIS creates a DID for the organization a, which may be created based on a public key sent by the organization a, for example, by calculating the public key of the organization a using a Hash function, or may be created according to other information of the organization a (which may or may not include the public key). The latter may require that institution a provide some information beyond the public key. Thereafter, agency a may provide an authentication function, thereby proving itself to the other party as agency a. Fig. 3 is a flowchart of a method for verifying identity of an organization by a server in an embodiment of the present specification, including:

s301: the agency device 100 of agency a initiates a DID creation request to DIS, where the request includes the public key of agency a.

S303: in response to the creation request, the DIS creates a DID and a corresponding DIDdoc for the agency a after the agency information (such as the qualification, the certificate, and the like) of the agency a passes verification, and sends the DID and the corresponding DIDdoc to a blockchain platform for saving. The DIDdoc includes the public key of the organization a. The DIDdoc also includes information such as a download address of verifiable proof of identity of organization a.

S305: the blockchain platform receives a verification request sent by a server, wherein the verification request comprises the DID of the organization A.

S307: and the block chain platform takes the DIDdoc corresponding to the DID from the self storage and returns the DIDdoc to the server.

S309: the server generates a character string and transmits the character string to the agency device 100 of the agency a.

S311: the institution device 100 signs the string with the private key of institution a and returns to the server.

S313: and the server verifies whether the returned signature is correct or not by using the received public key in the DIDdoc, and if so, the identity of the organization A is confirmed.

The server 400 may perform the risk data sharing method shown in fig. 4 after authentication of the organization is passed.

As shown in fig. 4, first, in step S401, the agency device 100 transmits a ciphertext risk data file F3 to the server 400.

The server 400 may request the ciphertext risk data file from each organization device at regular intervals, and the organization device 100 may transmit the file F3 generated through the flow shown in fig. 2 to the server 400 in response to the request of the server. Specifically, the organization apparatus 100 may sign the document F3 using the private key of the DID of the organization a, and transmit the DID of the organization a (e.g., DIDa), the document F3, and the signature of the document F3 by the private key of DIDa to the server 400.

In step S403, the server 400 provides the TEE with the ciphertext risk data files (including file F3) corresponding to the DID of each organization.

After receiving the ciphertext risk data file from each mechanism device, the server 400 may store the ciphertext risk data file in a storage server inside or outside the server, and obtain a storage address of the ciphertext risk data file.

Thereafter, the server 400 may send to the TEE the DID lists of the various institutions and the file addresses and public keys of the ciphertext risk data files corresponding to the various DIDs. The TEE can read the ciphertext risk data file corresponding to each DID from the file address corresponding to each DID. The public key of each organization is subsequently used for encrypting the file sent to the organization, and it can be understood that the TEE is not limited to encrypting the file sent to the organization by using the public key of the organization, but may use any key negotiated by the TEE and the organization device or the server and the organization device, including a symmetric key and an asymmetric key.

In one embodiment, the server 400 may send the DID list of each organization and the file address and the public key of the ciphertext risk data file corresponding to each DID to the TEE after the signature verification of the ciphertext risk data file of each organization passes.

In one embodiment, the server may provide a plurality of signatures of the plurality of institution devices to the trusted unit, so that the trusted unit first verifies the plurality of signatures using public keys of the plurality of institutions, respectively, before decrypting the plurality of ciphertext risk data files, respectively, and decrypts the plurality of ciphertext risk data files if verification is successful.

At step S405, the TEE generates a risk union file F4.

Specifically, after acquiring the ciphertext risk data files of each mechanism, the TEE decrypts each ciphertext risk data file by using its own private key, thereby acquiring the risk data files (including the risk data file F2) of each mechanism. Thereafter, the TEE may generate a risk union file F4 based on the risk data files of the various institutions. The risk union set file F4 includes a plurality of rows, which correspond to all risk users included in the plurality of organizations, respectively, each row including a user ID, a risk tag set, and an organization set, where the risk tag set is obtained from the plurality of risk data files, and the organization set includes organization identifiers of organizations that provide risk tags.

Fig. 5 is a schematic process diagram of generating a risk union file F4 in an embodiment of the present specification. The upper part of fig. 5 schematically shows the risk data files of the respective organizations, wherein the risk data file of the organization a corresponds to the organization identifier DIDa of the organization a, the risk data file of the organization B corresponds to the organization identifier DIDb of the organization B, and the risk data file of the organization C corresponds to the organization identifier DIDc of the organization C. The user IDs of the risky users in the respective institutions and the corresponding risk labels are shown in the respective risk data files, and the plurality of lines in the risk data files are arranged in ascending order of the user IDs.

In the TEE, when merging processing is performed on a plurality of risk data files, as shown in fig. 5, a minimum user ID is first indicated with a pointer for each risk data file. Among the user IDs indicated by the pointers in the three risk data files in fig. 5, the user ID of organization a is the smallest ID, and therefore, ID1{ risk1} { DIDa }, i.e., { risk1} is a risk label set of ID1 in the plurality of risk data files, and { DIDa } is a set of organization identifications providing labels in the risk label set, are written in line 1 in the risk union file shown in the lower part of fig. 5.

After noting the information corresponding to ID1 in the risk union file, a pointer is pointed to the next line, i.e., the line corresponding to ID3, in the risk data file of agency a, and the above-described process is repeated. Specifically, after the minimum ID indicated by the three pointers is determined to be ID2 in the TEE, information "ID2{ risk2, riskL } { DIDb, DIDc }" corresponding to ID2 is recorded on line 2 in the risk union document. After traversing all the rows in each risk data file using the fingers through the same process as described above, the risk union file F4 shown in the lower part of fig. 5 can be obtained.

In step S407, the TEE performs desensitization processing on the user identifier in the risk union file F4, and writes the desensitized user identifier in the risk user file F5.

The TEE may create a risky user file F5 to record therein a list of risky users before desensitizing the user identification in the risky union file F4.

In one embodiment, the TEE may obtain a salt value to salt the user identification, e.g., the TEE may calculate a hash value of file F4 as the salt value. The TEE may then encrypt the concatenation of the user identification (i.e., ID) and the salt value to obtain a desensitized user identification. Wherein the TEE may encrypt the splice value using a symmetric key or may encrypt the splice value using a public key of the TEE.

In another embodiment, the TEE may sign the splice value using the TEE private key, with the obtained signature as a desensitized user identification.

In another embodiment, the TEE may sign the above-described splice value using the TEE private key and compute a hash value on the obtained signature, with the hash value as the desensitized user identification.

After acquiring the desensitized user identity, the TEE records the desensitized user identity in the risk user list in file F5. The TEE completes the generation of file F5 after completing the processing for the user identification in each row in file F4 as described above. The completed file F5 includes therein a plurality of desensitized user identities.

In addition, the TEE, after determining the salt value used to generate file F5, may encrypt the salt value using the TEE public key to obtain a salt value ciphertext, and send the salt value ciphertext to server 400. After receiving the salt cipher text, the server 400 may store the salt cipher text in the blockchain.

At step S409, the TEE sends file F5 to server 400.

Specifically, the TEE stores the file F5 outside the TEE (i.e., the EPC), for example (for example, a storage medium in the server 400 or a storage server other than the server 400), and transmits the storage address of the file F5 to the server 400, so that the server 400 can read the file F5.

In step S411, the server 400 stores the file F5 in the block chain.

Specifically, server 400 may store file 5 into the blockchain by sending a transaction that includes file 5 to the blockchain. That is, each node in the blockchain stores the transaction in the blockdatabase after executing the transaction, thereby storing the file F5 in the blockchain. By storing the file F5 into the blockchain, the file F5 is saved in the blockchain without being tampered. Meanwhile, because the file F5 comprises the desensitized user identification, the user privacy can not be revealed.

Fig. 6 is a flowchart of a method for generating a risk query file ciphertext at an institution device in an embodiment of the present disclosure. The mechanism apparatus in fig. 6 may be any one of the plurality of mechanism apparatuses in fig. 1. The mechanism apparatus 100 is described below as an example.

As shown in fig. 6, first, in step S601, the agency device 100 acquires initial query data including identity information of a user to be queried.

In the organization a corresponding to the organization device 100, when the organization administrator processes the business, the risk data query may need to be performed on the users in the current business in real time, so as to reduce the business risk. To this end, the organization administrator may input the identity information of the user to be queried in real time into the organization device 100 for generating the initial query data. In this scenario, the query speed requirement is high. The identity information of the user includes, for example, a name, a certificate number, and the like. Specifically, the user identity information may be in the following form: "name/certType/certNum", wherein name is user name, certType is certificate type, certNum is certificate number, and the three form three elements of user identity information.

In step S603, the agency device 100 determines whether a user ID corresponding to the identity information is stored locally.

After the mechanism device 100 receives the initial query data, in order to protect the privacy of the user, desensitization processing needs to be performed on the user identity information to be queried, that is, the identity information of the user cannot be directly included in the query request sent from the mechanism device 100. Therefore, each organization only needs to use the same user ID for the same user to replace the identity information of the user. Specifically, for the identity information of the user to be queried, the client in the mechanism device 100 first determines whether a user ID corresponding to the identity information is stored locally. For example, the client may determine whether the identity information and the corresponding user ID are included in a mapping table of a preset address in the hard disk. If not, the client may perform step S605, requesting the user ID of the user from the server 400.

In step S605, the facility device 100 requests the user ID of the user from the server 400.

Specifically, since the server 400 is also not fully trusted, the agency device 100 also needs to desensitize the three-factor information of the user when requesting the user ID from the server 400. Specifically, the agency device 100 may calculate a hash value of the three-factor information, hash1= hash (name + certType + certNum), where "+" may indicate sequential concatenation of two items of data, and then the agency device 100 may send the hash value hash1 to the server 400 to request the user ID corresponding to the hash value.

In step S607, the server 400 returns the user ID of the user to the agency device 100.

After determining the user ID, the server returns the user ID to the agency device 100. By doing so, the facility device 100 uses the user ID for one user in the query file it sends to the server in agreement with the user ID of the user in the previous risk union file, so that the risk information of the user can be queried in the risk union file based on the user ID.

In step S609, the facility device 100 stores the user identification information and the user ID in association.

This step can refer to the above description of step S209, and is not described herein again.

In step S611, the agency device 100 generates query data including the acquired user ID, and encrypts the query data to obtain ciphertext query data.

In the case where the agency device 100 determines in step S603 that the user ID corresponding to the identity information is stored locally (for example, in the mapping table described above), step S611 may be directly performed. Alternatively, the mechanism apparatus 100 may perform step S611 after performing step S609.

Specifically, the agency device 100 may generate a random character string as a salt value, and encrypt concatenation data of the user ID and the salt value using the TEE public key, thereby generating a ciphertext including the user ID information. It will be appreciated that the authority device is not limited to encrypting the splice data using the TEE public key, but may encrypt the splice data using other symmetric and asymmetric keys negotiated with the TEE.

Fig. 7 is a flowchart of a risk data query method in an embodiment of the present specification.

As shown in fig. 7, the organization device 100 transmits the above-generated ciphertext query data to the server 400 in step S701.

Specifically, the organization device 100 may sign the ciphertext query data using its own private key, and send the DID (e.g., DIDa) of the organization device 100, the ciphertext query data, and the signature of the ciphertext by the private key of DIDa to the server 400. So that the server 400 can verify the signature to verify the corresponding agency identity of the agency device 100.

In step S703, the server 400 provides the ciphertext query data to the TEE.

The server 400, after receiving the ciphertext query data including the user ID information from the mechanism device 100, may store the ciphertext query data in a storage server inside or outside the server, and acquire a storage address of the ciphertext query data. The server 400 may then send the storage address of the ciphertext query data to the TEE. So that the TEE can read ciphertext query data from the memory address. The server 400 may also send the ciphertext query data directly to the TEE.

In step S705, the TEE generates a desensitized user identification based on the ciphertext query data.

Specifically, after obtaining ciphertext query data including user ID information, the TEE decrypts the ciphertext query data using its own private key, and obtains the user ID from the decrypted data. Thereafter, the TEE may generate a desensitized user identification corresponding to the user ID using the same method as the desensitized user identification in the generation file F5.

Specifically, the server 400 may query the above-described salt ciphertext for generating the desensitized user identification in the file F5 from the blockchain and provide the salt ciphertext to the TEE. And after obtaining the salt value ciphertext, the TEE decrypts the salt value ciphertext by using a private key of the TEE to obtain a salt value used when generating the file F5, and generates a desensitization user identifier corresponding to the user ID based on the salt value.

In step S707, the TEE sends the generated desensitized user identification to the server 400.

In step S709, the server 400 queries the blockchain request whether the desensitized user identification is in the risky user file F5.

In particular, the server 400 may send a transaction to any node in the blockchain, or a particular node, invoking an inquiry contract for inquiring whether the desensitized user identification is in the risky user file F5.

In step S711, the blockchain returns the query result to the server 400.

The above node of the blockchain executes the transaction after receiving the above transaction, thereby reading the file F5 stored in the blockchain to determine whether the desensitized user identification of the user to be queried is included in the file F5. After the query result is obtained, the query result is returned to the server 400.

In step S713, the server 400 determines whether the desensitized user identification is in the file F5 according to the query result.

In the case where the query result indicates that the desensitized user identification is not in the file F5, the server 400 executes step S715 to return the query result that the user is not at risk to the institution device 100. By combining the TEE and the risk user file stored in the block chain, whether the user to be inquired is risk-free or not can be quickly determined, the feedback speed is improved, and the user experience is improved.

In the case where the query result indicates that the desensitized user identification is in file F5, server 400 performs the process in flow 800 shown in fig. 8.

Fig. 8 is a flowchart of a risk data query method in an embodiment of the present specification.

As shown in fig. 8, in step S801, the server 400 instructs the TEE to make a query to the user.

Specifically, the server 400 may provide public keys of other institutions and the above-described ciphertext including the user ID to the TEE to instruct the TEE to perform the user query.

The other institution is an institution device in the system other than the institution device 100 that originated the query. Specifically, the server 400 may send, for example, the storage address of the file including the public key of each organization to the TEE so that the TEE may obtain the public keys of each other organization. The public key of each other institution is used to encrypt the query request sent to the institution, and it is understood that the TEE is not limited to encrypting the query request sent to the institution by using the public key of the institution, but may use any key negotiated by the TEE with the institution device or the server with the institution device, including a symmetric key and an asymmetric key.

In step S803, the TEE generates ciphertext query requests corresponding to each of the other organizations

For each other organization, the TEE may encrypt the user ID corresponding to the ciphertext query data using the organization public key to obtain the ciphertext query request.

Specifically, the TEE may encrypt the user ID using the public key of the organization to obtain the ciphertext query request.

In step S805, the TEE transmits ciphertext query requests corresponding to the respective other institutions to the server 400.

In step S807, the server 400 transmits the ciphertext query request to each of the other institution apparatuses.

In step S809, the other organization device returns the ciphertext query result to the server 400.

After receiving the ciphertext query request, the other mechanism devices decrypt the ciphertext query request by using the private key of the mechanism to obtain the user ID, and locally query the risk label corresponding to the user ID. If the risk label corresponding to the user ID is not queried, the public key of the TEE can be used for encrypting preset data (such as a character string VALID) to obtain a ciphertext query result. If the risk label corresponding to the user ID is inquired, a random character string can be generated, and the joint value of the risk label and the random character string is encrypted by using the public key of the TEE to obtain a ciphertext inquiry result.

In step S811, the server 400 provides the received ciphertext query results of the respective other institutions to the TEE.

In step S813, the TEE aggregates the risk tags of the respective organizations, generating a ciphertext risk tag set.

Specifically, after receiving ciphertext query results of other mechanisms, the TEE decrypts the ciphertext query results by using a private key of the TEE, and summarizes the query results, thereby generating a risk tag set, where the risk tag set includes one or more risk tags corresponding to the user ID. And then, the TEE encrypts the risk label set by using the public key of the mechanism A to obtain a ciphertext risk label set.

At step S815, the TEE provides the ciphertext risk tag set to the server 400.

In step S817, the server 400 provides the ciphertext risk tag set to the organization device 100.

In step S819, after receiving the ciphertext risk tag set, the mechanism device 100 decrypts the ciphertext risk tag set using its own private key to obtain a risk tag set corresponding to the user ID, so that service processing can be performed based on the risk tag set.

In the embodiment of the description, by combining the server, the TEE and the block chain to execute the risk data query method, the mechanism device performs desensitization, encryption and other processing on information of a user to be queried to obtain a user identifier and sends the user identifier to the server, the server provides the user identifier to the TEE, and the TEE further adopts a preset algorithm to process the user identifier to obtain the desensitization user identifier, so as to query whether a risk user list stored in the block chain includes the desensitization user identifier or not, so that the user privacy is protected, and the query speed in a real-time query scene is improved while compliance requirements in a service scene are met.

Although the risk data query scheme implemented by combining the server and the TEE is described above, the embodiments of the present specification are not limited thereto. A risk data query scheme implemented by a TEE in another embodiment of this specification will be described below by fig. 9 and 10.

Fig. 9 is a flowchart of a risk data query method in an embodiment of the present specification.

As shown in fig. 9, in step S901, the agency device 100 transmits the above ciphertext query data to the TEE.

Specifically, the organization device 100 may use its own private key to sign the ciphertext query data, and send the DID (e.g., DIDa) of the organization device 100, the ciphertext query data, and the signature of the ciphertext query data by the private key of DIDa to the TEE. Public keys of various organizations may be stored in the TEE in advance, or public keys of various organizations may be acquired from the outside of the TEE, for example, a public key of DIDa is queried from a block chain. The TEE may thus verify the signature to verify the corresponding authority identity of the authority device 100.

In step S903, the TEE generates a desensitized user identification based on the ciphertext query data.

Specifically, after obtaining the ciphertext query data, the TEE decrypts the ciphertext query data by using its own private key, and obtains the user ID from the data obtained by decryption. Thereafter, the TEE may generate a desensitized user identification corresponding to the user ID using the same method as that used to generate the desensitized user identification in file F5.

Specifically, the TEE may query the above-mentioned salt ciphertext used to generate the desensitization user identification in file F5 from the blockchain, and the salt ciphertext may be uploaded to the blockchain by the TEE when file F5 is generated. And then, the TEE decrypts the salt value ciphertext by using a private key of the TEE to obtain a salt value used when the file F5 is generated, and generates a desensitization user identifier corresponding to the user ID based on the salt value.

In step S905, the TEE requests a query from the blockchain whether the desensitized user identification is in the risky user file F5.

In particular, the TEE may send a transaction to any node in the blockchain or a particular node invoking an inquiry contract for inquiring whether the desensitized user identification is in the risky user file F5.

In step S907, the blockchain returns the query results to the TEE.

The above node of the blockchain executes the transaction after receiving the above transaction, thereby reading the file F5 stored in the blockchain to determine whether the desensitized user identification of the user to be queried is included in the file F5. After the query result is obtained, the query result is returned to the TEE.

In step S909, the TEE determines whether the desensitized user identification is in the file F5 according to the query result.

In the case where the query result indicates that the desensitized user identity is not in the file F5, the TEE performs step S911, returning the query result that the user is not at risk to the agency device 100. By combining the TEE and the risk union set file stored in the block chain, whether the user to be inquired is risk-free or not can be quickly determined, the feedback speed is increased, and the user experience is improved.

In the case where the query result indicates that the desensitized user identification is in file F5, the TEE performs the process in flow 1000 shown in fig. 10.

Fig. 10 is a flowchart of a risk data query method in an embodiment of the present specification.

As shown in FIG. 10, at step S1001, the TEE generates ciphertext query requests corresponding to various other institutions

For each other organization, the TEE may encrypt the obtained user ID using the public key of the organization to obtain the ciphertext query request.

In step S1003, the TEE transmits ciphertext query requests corresponding to the respective other institutions.

In step S1005, each of the other organization devices returns the ciphertext query result to the TEE.

In step S1007, the TEE aggregates the risk data of each organization, and generates a ciphertext risk label set.

Specifically, after receiving ciphertext query results of other mechanisms, the TEE decrypts the ciphertext query results by using a private key of the TEE, and summarizes the query results, thereby generating a risk tag set, where the risk tag set includes one or more risk tags corresponding to the user ID. And then, encrypting the risk label set by using the public key of the mechanism A by the TEE to obtain a ciphertext risk label set.

In step S1009, the TEE provides the ciphertext risk tag set to the institution apparatus 100.

The TEE may store the ciphertext risk tag set in a storage server and send a storage address to the facility device 100, so that the facility device 100 may read the ciphertext risk tag set. Alternatively, the TEE may send the ciphertext risk tag set directly to the institution device 100.

In step S1011, after receiving the ciphertext risk tag set, the mechanism device 100 decrypts the ciphertext risk tag set by using its own private key, to obtain a risk tag set corresponding to the user ID, so that the business processing can be performed based on the risk tag set.

In the embodiment of the description, by combining the TEE and the block chain to execute the risk data query method, the mechanism device performs desensitization, encryption and other processing on information of a user to be queried to obtain a user identifier and sends the user identifier to the TEE, and the TEE further performs processing on the user identifier by using a preset algorithm to obtain the desensitization user identifier, so as to query whether a risk user list stored in the block chain includes the desensitization user identifier, thereby protecting user privacy and meeting compliance requirements in a service scene, and improving query speed in a real-time query scene.

Fig. 11 is an architecture diagram of a server in an embodiment of the present specification, where the server is configured to execute the method shown in any one of fig. 2 to 8, and the server includes:

a receiving unit 111, configured to receive ciphertext query data from a first mechanism device, where the ciphertext query data is obtained by encrypting query data, the query data includes a first user identifier of a first user to be queried, and the first mechanism device belongs to a first mechanism;

a providing unit 112, configured to provide the ciphertext query data to the TEE;

the receiving unit 111 is further configured to: receiving a second user identification of the first user from the TEE, wherein the second user identification of the first user is obtained by processing the first user identification of the first user through a preset algorithm;

a sending unit 113, configured to send, to the blockchain, an inquiry request for inquiring whether the second user identifier of the first user is included in a risk user list stored in the blockchain, where the risk user list is generated based on multiple risk data from multiple organizations and includes the second user identifiers of multiple risk users;

the receiving unit 111 is further configured to receive a query result from the blockchain;

a returning unit 114, configured to, when it is determined that the risk user list does not include the second user identifier of the first user according to the query result, return first information to the first mechanism device, where the first information is used to indicate that the first user is not a risk user.

Fig. 12 is an architecture diagram of a trusted unit in an embodiment of the present specification, where the trusted unit is configured to execute the method shown in fig. 9 or fig. 10, and the trusted unit includes:

a receiving unit 121, configured to receive ciphertext query data from a first mechanism device, where the ciphertext query data is obtained by encrypting query data, the query data includes a first user identifier of a first user to be queried, and the first mechanism device belongs to a first mechanism;

a decryption unit 122, configured to decrypt the ciphertext query data, obtain a first user identifier of the first user, and process the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user;

a sending unit 123, configured to send, to the blockchain, an inquiry request for inquiring whether a second user identifier of the first user is included in a risk user list stored in a blockchain, where the risk user list is generated based on multiple risk data from multiple organizations and includes the second user identifiers of multiple risk users;

the receiving unit 121 is further configured to receive a query result from the blockchain;

a returning unit 124, configured to, when it is determined that the second user identifier of the first user is not included in the risk user list according to the query result, return first information to the first mechanism device, where the first information is used to indicate that the first user is not a risk user.

Embodiments of the present specification also provide a computer-readable storage medium on which a computer program is stored, which, when executed in a computer, causes the computer to perform the method shown in any one of fig. 2 to 10.

Embodiments of the present specification further provide a trusted unit, including a memory and a processor, where the memory stores executable code, and the processor executes the executable code to implement the method shown in any one of fig. 2 to 10.

Embodiments of the present specification further provide a server, including a memory and a processor, where the memory stores executable codes, and the processor executes the executable codes to implement the method shown in any one of fig. 2 to 8.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain a corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical blocks. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as ABEL (Advanced Boolean Expression Language), AHDL (alternate Hardware Description Language), traffic, CUPL (core universal Programming Language), HDCal, jhddl (Java Hardware Description Language), lava, lola, HDL, PALASM, rhyd (Hardware Description Language), and vhigh-Language (Hardware Description Language), which is currently used in most popular applications. It will also be apparent to those skilled in the art that hardware circuitry for implementing the logical method flows can be readily obtained by a mere need to program the method flows with some of the hardware description languages described above and into an integrated circuit.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a server system. Of course, this application does not exclude that with future developments in computer technology, the computer implementing the functionality of the above described embodiments may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device or a combination of any of these devices.

Although one or more embodiments of the present description provide method operational steps as described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive approaches. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or end product executes, it may execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the method shown in the embodiment or the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. For example, if the terms first, second, etc. are used to denote names, they do not denote any particular order.

For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, when implementing one or more of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, etc. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage, graphene storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

As will be appreciated by one skilled in the art, one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the system embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and reference may be made to the partial description of the method embodiment for relevant points. In the description of the specification, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

The above description is merely exemplary of one or more embodiments of the present disclosure and is not intended to limit the scope of one or more embodiments of the present disclosure. Various modifications and alterations to one or more embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present specification should be included in the scope of the claims.

Claims

1. A risk data query method, comprising:

the server provides the ciphertext query data to a trusted unit for privacy data processing;

the server sends a first query request to the blockchain, and is used for querying whether a second user identifier of the first user is included in a risk user list stored in the blockchain, wherein the risk user list is generated based on a plurality of risk data from a plurality of organizations and comprises the second user identifiers of a plurality of risk users;

the block chain inquires whether the risk user list comprises a second user identifier of the first user according to the first inquiry request, and returns the inquiry result to the server;

2. The method of claim 1, further comprising:

the multiple mechanism devices send ciphertext risk data of mechanisms to which the multiple mechanism devices belong to the server;

the trusted unit acquires a plurality of ciphertext risk data of the plurality of mechanisms from the server, respectively decrypts the ciphertext risk data to obtain a plurality of risk data, wherein the risk data comprise a user identifier and a risk tag corresponding to the user identifier; generating the list of risky users based on the plurality of risk data; providing the list of at-risk users to the server;

the server stores the list of risky users into the blockchain.

3. The method of claim 1 or 2, further comprising:

when the server determines that the risk user list comprises the second user identification of the first user according to the query result, the server instructs the trusted unit to query according to the ciphertext query data;

the trusted unit generates a second query request, wherein the second query request comprises a first user identifier of the first user, and encrypts the second query request to generate ciphertext query requests respectively corresponding to a plurality of second mechanisms; sending each ciphertext query request to each second mechanism;

each second mechanism decrypts the ciphertext query request to obtain a first user identifier, queries the risk tag of the first user based on the first user identifier to obtain a query result, encrypts the query result to obtain a ciphertext query result, and sends the ciphertext query result to the server;

the server provides the ciphertext query result of each second organization to the trusted unit;

the trusted unit decrypts the ciphertext query result of each second mechanism to obtain a plurality of query results, generates a risk label set of the first user based on the plurality of query results, and encrypts the risk label set to obtain a ciphertext risk label set; sending the ciphertext risk tag set to the server;

the server providing the ciphertext risk tag set to the first mechanism device;

and the first mechanism equipment decrypts the ciphertext risk label set to obtain the risk label set of the first user.

4. The method of claim 1 or 2, the first subscriber identity comprising: and carrying out hash calculation on one or more items of information of the first user to obtain a digest value.

5. The method of claim 4, further comprising: the first mechanism device calculates a first hash value of one or more items of information of a first user, and sends the first hash value to the server;

the server calculates a second hash value of the first hash value and a preset value as a first user identifier of the first user, and returns the first user identifier to the first mechanism device;

and the first mechanism equipment stores the corresponding relation between the first user identification and one or more items of information of the first user.

6. The method of claim 3, further comprising: the server, after receiving the plurality of ciphertext risk data from the plurality of institution devices, storing the ciphertext risk data for each institution in association with an institution identification for each institution, providing a storage address for each ciphertext risk data to the trusted unit,

the trusted unit acquiring a plurality of ciphertext risk data of the plurality of organizations through the server comprises: and the trusted unit acquires the plurality of ciphertext risk data based on each storage address.

7. The method of claim 3, wherein the plurality of organization devices sending ciphertext risk data of the organizations to which they belong to the server further comprises: the method comprises the following steps that a plurality of institution devices send DID and ciphertext risk data of institutions to which the institution devices belong to a server, and the method further comprises the following steps: the server obtains public keys for the DIDs of the plurality of institutions from the blockchain.

8. The method of claim 7, further comprising: the server providing a public key of the first organization to the trusted unit, the trusted unit encrypting the set of risk tags comprising: the trusted unit encrypts the set of risk tags using a public key of the first authority.

9. The method of claim 2, the preset algorithm comprising any one of:

splicing the first user identification with a preset character string, symmetrically encrypting the spliced character string, and taking a ciphertext obtained by encryption as the second user identification;

splicing the first user identification with a preset character string, encrypting the spliced character string by using a trusted unit public key, and taking a ciphertext obtained by encryption as the second user identification;

splicing the first user identification with a preset character string, signing the spliced character string by using a trusted unit private key, and taking the obtained signature as the second user identification;

and splicing the first user identification with a preset character string, signing the spliced character string by using a trusted unit private key, calculating a hash value of the obtained signature, and taking the hash value as the second user identification.

10. The method of claim 9, generating the list of risky users based on the plurality of risk data comprises: determining the preset character string, generating the risk user list based on the plurality of risk data through the preset algorithm, encrypting the preset character string to obtain a ciphertext character string, storing the ciphertext character string into a block chain,

the method further comprises the step that the trusted unit obtains the ciphertext character string from the block chain and decrypts the ciphertext character string to obtain the preset character string before processing the first user identifier of the first user through a preset algorithm.

11. A risk data query method, comprising:

the trusted unit decrypts the ciphertext query data to obtain a first user identifier of the first user, and processes the first user identifier of the first user through a preset algorithm to obtain a second user identifier of the first user; sending a first query request to the blockchain for querying whether a second user identifier of the first user is included in a risk user list stored in the blockchain, wherein the risk user list is generated based on a plurality of risk data from a plurality of organizations and comprises the second user identifiers of a plurality of risk users;

the block chain inquires whether the risk user list comprises a second user identifier of the first user or not according to the first inquiry request, and returns the inquiry result to the trusted unit;

12. The method of claim 11, further comprising:

when the trusted unit determines that the risk user list comprises a second user identifier of the first user according to the query result, the trusted unit generates a second query request, wherein the second query request comprises the first user identifier of the first user, encrypts the second query request and generates ciphertext query requests corresponding to each second organization; sending each ciphertext query request to each second mechanism;

each second mechanism decrypts the ciphertext query request to obtain a first user identifier, queries the risk label of the first user based on the first user identifier to obtain a query result, encrypts the query result to obtain a ciphertext query result, and sends the ciphertext query result to the trusted unit;

the trusted unit decrypts the ciphertext query result of each second mechanism to obtain a plurality of query results, generates a risk label set of the first user based on the plurality of query results, and encrypts the risk label set to obtain a ciphertext risk label set; sending the ciphertext risk tag set to the first mechanism device;

13. A risk data query method, performed by a server, the method comprising:

providing the ciphertext query data to a trusted unit;

receiving a second user identifier of the first user from the trusted unit, wherein the second user identifier of the first user is obtained by processing the first user identifier of the first user through a preset algorithm;

receiving query results from the blockchain;

14. A method of risk data querying, performed by a trusted unit, comprising:

receiving query results from the blockchain;

15. A risk data query system comprises a first mechanism device, a server, a block chain system and a trusted unit for processing private data,

the server is used for providing the ciphertext query data to a trusted unit;

16. A server, the server comprising:

17. A trusted unit, comprising:

a sending unit, configured to send, to the blockchain, an inquiry request for inquiring whether a second user identifier of the first user is included in a risk user list stored in a blockchain, where the risk user list is generated based on multiple risk data from multiple organizations and includes the second user identifiers of multiple risk users;

18. A computer-readable storage medium, on which a computer program is stored which, when executed in a computer, causes the computer to carry out the method of claim 13 or 14.