Sensitive data security association analysis method and device based on security multi-party computing

By using role definition policies, communication certificates, encryption technology and audit tracking systems in the cloud computing environment, the security of multi-participant data correlation analysis is achieved, and how sensitive data can be associated with privacy in the cloud computing environment is solved. Analyzing issues improves data security and integrity.

CN119272302AActive Publication Date: 2025-01-07CHINA MOBILE GRP GUANGDONG CO LTD

Patent Information

Application Number
CN202411373417.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-09-29
Publication Date
2025-01-07
Estimated Expiration
2044-09-29

AI Technical Summary

Technical Problem

In a cloud computing environment, when multiple participants need to conduct correlation analysis of the sensitive data they hold, how to achieve data correlation analysis on the premise of protecting the data privacy of each party to prevent the problem of sensitive data leakage.

Method used

Create roles and grant permissions through role definition policies, realize identity authentication and authorization management based on communication certificates and key pairs, establish a secure communication tunnel, encrypt sensitive data, and decrypt the policy in the predefined calculation process based on the preset correlation decryption policy partial decryption is carried out, and an audit trail system is deployed to record data access and processing behaviors.

Benefits of technology

When conducting data correlation analysis by multiple participants, protect the privacy of all parties, prevent sensitive data leakage, improve the security of sensitive data correlation analysis, and ensure the security and integrity of data processing through monitoring and erasure coding technologies.

✦ Generated by Eureka AI based on patent content.

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Abstract

The invention relates to a sensitive data security association analysis method and device based on security multi-party computing. The method comprises the following steps: creating a plurality of roles and endowing the roles with permissions; identity authentication and authorization management between participants are realized; establishing a secure communication tunnel for the participant; sensitive data of participants are encrypted, and the data are partially decrypted only in a predefined calculation process; and capturing and recording data access and processing behaviors. According to the invention, after the identity authentication of each participant carrying out data association analysis is successful, the secure communication tunnel is established for the participant, the sensitive data of each participant is encrypted, and the necessary data is partially decrypted only in the predefined necessary calculation process. And meanwhile, the audit tracking system captures and records data access and processing behaviors, so that the privacy of each party is protected when multiple participants carry out data association analysis, the sensitive data is prevented from being leaked, and the effect of improving the security of sensitive data association analysis is achieved.
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Description

Technical Field

[0001] The present application relates to the technical field of sensitive data security, and in particular to a method and device for sensitive data security association analysis based on secure multi-party computing. Background Art

[0002] With the rapid development of random information technology, data information has become increasingly important, especially in various industries, such as genetic disease research and satellite trajectory measurement, where correlation analysis based on sensitive data is playing a vital role. However, given that these data may contain highly confidential information of individuals or companies, once leaked, they may be maliciously used by criminals. Therefore, strict security protection measures must be taken when processing and using these data.

[0003] In a cloud computing environment, multiple participants need to perform correlation analysis on the sensitive data they hold, but at the same time ensure that data privacy is not leaked. This creates a technical contradiction in how to achieve data correlation analysis while protecting the data privacy of all parties. Summary of the invention

[0004] In order to protect the privacy of all parties when multiple parties conduct data association analysis, prevent the leakage of sensitive data, and thereby improve the security of sensitive data association analysis, the present application provides a sensitive data security association analysis method and device based on secure multi-party computing.

[0005] The above-mentioned invention objective of the present application is achieved through the following technical solutions:

[0006] A method for sensitive data security association analysis based on secure multi-party computing, characterized by comprising the steps of:

[0007] Create several roles through role definition strategy and grant them corresponding permissions;

[0008] Realize identity authentication and authorization management between participants based on communication certificates and key pairs;

[0009] When the identity authentication between the participants is successful, a secure communication tunnel for data transmission encryption channel is established for the participants with successful identity authentication;

[0010] Encrypt the sensitive data of the participants, and based on the preset correlation decryption strategy, only partially decrypt the associated data in the predefined calculation process;

[0011] Deploy an audit tracking system to capture and record data access and processing behaviors, and generate an audit log that cannot be tampered with.

[0012] By adopting the above technical solution, roles are defined and permissions are allocated through pre-deployed role definition strategies, thereby ensuring that data access and operations are subject to appropriate restrictions; the participants are authenticated with each other and authorized to manage the participants, thereby ensuring that the identities of the participants are authentic and that their operations comply with the permissions granted to them; when the identity authentication between the participants is successful, a secure communication tunnel for data transmission is established for these participants; the data of the participants is encrypted to protect their data privacy, and at the same time, it is allowed to partially decrypt only the required data based on the preset correlation decryption strategy during the predefined calculation process, thereby Meet specific analysis needs; deploy an audit tracking system to capture data access and processing behaviors, and generate an unalterable audit log to ensure the traceability and auditability of system operations; this application establishes a secure communication tunnel for each participant in the data association analysis after successful identity authentication, and encrypts the sensitive data of each participant, and only partially decrypts the necessary data during the predefined required calculation process. At the same time, the audit tracking system is used to capture and record data access and processing behaviors, so as to protect the privacy of all parties when multiple parties conduct data association analysis, prevent the leakage of sensitive data, and thus improve the security of sensitive data association analysis.

[0013] In a preferred example, the present application can be further configured as follows: the steps of implementing identity authentication and authorization management between participants based on communication certificates and key pairs include the following steps:

[0014] Obtain the communication certificate of each participant and verify its validity for identity authentication;

[0015] Based on the identity information in the communication certificate, the corresponding role is matched for each participant, thereby realizing the authorization management of the participants.

[0016] By adopting the above technical solution, the communication certificate of each participant is obtained, and its validity is verified by checking whether the communication certificate is expired, verifying the signature, verifying the domain name, etc. After completing the identity authentication, the corresponding role is matched for the participant based on the identity information in the communication certificate, thereby granting it the corresponding authority and completing the authorization management.

[0017] In a preferred example, the present application may be further configured as follows: when the identity authentication between the participants is successful, the step of establishing a secure communication tunnel for the participants with successful identity authentication for the encrypted channel for data transmission includes the following steps:

[0018] When the identity authentication between the participants is successful, the public key certificates are exchanged between the participants;

[0019] Based on the public key certificates obtained by each participant, each participant generates a shared key through a key exchange protocol;

[0020] Based on the shared key, each participant obtains a session key used to encrypt all communication data in the session.

[0021] By adopting the above technical solution, when the identity authentication between the participants is successful, the participants exchange their public key certificates and generate a shared key through the key exchange protocol based on the obtained public key certificates as the basis for subsequent encrypted communications. Based on the shared key, each participant obtains a session key for encrypting all communication data in the session, and uses the session key to enable each participant to establish a secure communication tunnel for an encrypted data transmission channel.

[0022] In a preferred example, the present application may be further configured as follows: the step of encrypting the sensitive data of the participant and partially decrypting the associated data only in a predefined calculation process based on a preset association decryption strategy includes the following steps:

[0023] Encrypt the sensitive data of all participants based on homomorphic encryption technology to obtain an encrypted data set;

[0024] Based on the pre-deployed correlation decryption strategy, the calculation steps in the calculation process are identified in real time;

[0025] When a predefined calculation step is identified, the data associated with the calculation step is partially decrypted.

[0026] By adopting the above technical solution, the data of all participants are encrypted using homomorphic encryption technology to obtain an encrypted data set. At the same time, the encrypted data set encrypted by the homomorphic encryption technology allows certain computing operations to be performed without decryption. Based on the pre-deployed associative decryption strategy, the computing process is monitored and identified in real time. When a predefined computing step is identified, the data associated with the step is partially decrypted for the current computing step. The present application deploys an associative decryption strategy to partially decrypt only the data associated with the identified predefined computing step, thereby decrypting the data to a minimum and keeping the computing steps in progress, which has the effect of improving the security of sensitive data protection.

[0027] In a preferred example, the present application may be further configured as follows: after the step of encrypting the sensitive data of the participant and partially decrypting only the associated data in the predefined calculation process based on the preset association decryption strategy, the following steps are performed:

[0028] Monitor computing nodes based on a preset monitoring mechanism, collect performance parameter information of computing nodes in real time, and record and update historical trend information;

[0029] When it is identified that the performance parameter information contains an abnormal vector, the computing node associated with the abnormal vector is set as an abnormal node;

[0030] Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node, send an activation instruction to the backup node, and load the task status of the abnormal node;

[0031] After the backup node is started, it obtains all sensitive data from the abnormal node and encrypts the obtained sensitive data;

[0032] Encode the tasks and data being processed based on erasure coding technology to obtain redundant data blocks;

[0033] The elasticity-based system protocol enables backup nodes to replace abnormal nodes and update the system configuration.

[0034] By adopting the above technical solution, during the calculation process, the computing nodes are monitored based on the preset monitoring mechanism, the performance parameter information of the computing nodes is collected in real time, and the historical trend information is recorded and updated. When an abnormal vector is identified, the computing node associated with the abnormal vector is set as an abnormal node, the computing environment of the abnormal node is synchronized to the pre-configured corresponding backup node, and the backup node is activated, the task status of the abnormal node is loaded, and after the backup node is started, all sensitive data of the abnormal node is obtained and decrypted, and the tasks and data being processed are encoded based on the erasure code technology to obtain redundant data blocks, and a flexible system protocol is given to enable the backup node to replace the abnormal node and update the system configuration; the present application By monitoring the computing nodes and marking the computing nodes associated with the abnormal vector as abnormal nodes when an abnormal vector is identified, the corresponding backup nodes are activated at the same time, and the computing environment and task status of the abnormal node are synchronized to the backup nodes. After the backup node is started, all sensitive data of the abnormal node is obtained and encrypted to ensure its security during transmission and storage. Based on the elastic system protocol, the backup node replaces the abnormal node. When the computing node abnormality is detected, the node is replaced and the data is recovered quickly, which has the effect of improving the security of data processing and ensuring data integrity. The erasure code technology is used to encode the tasks and data in processing to obtain redundant data blocks, thereby improving the fault tolerance and reliability of the data.

[0035] In a preferred example, the present application may be further configured as follows: when it is identified that the performance parameter information contains an abnormal vector, the step of setting the computing node associated with the abnormal vector as an abnormal node comprises the steps of:

[0036] When any parameter in the performance parameter information is lower than or higher than a corresponding preset threshold, the parameter is identified as an abnormal vector;

[0037] Record the monitoring occurrence time and response interval of the abnormal vector;

[0038] The identity information of the computing node associated with the abnormal vector is identified, and the computing node is set as an abnormal node.

[0039] By adopting the above technical solution, when any parameter in the performance parameter information is lower than or higher than the corresponding preset threshold, the parameter is identified as an abnormal vector, the monitoring occurrence time and response interval time of the abnormal vector are recorded to analyze the cause, the identity information of the computing node associated with the abnormal vector is identified and the computing node is marked as an abnormal node, ensuring more accuracy, efficiency and reliability in processing the abnormal vectors in the performance parameter information.

[0040] In a preferred example, the present application can be further configured as follows: the step of synchronizing the computing environment of the abnormal node to the pre-configured corresponding backup node, sending an activation instruction to the backup node, and loading the task status of the abnormal node includes the following steps:

[0041] Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node based on the computing environment snapshot technology;

[0042] Sending an activation instruction to the backup node so that the backup node starts based on the synchronized computing environment;

[0043] Based on the task save record, load the last saved task status on the abnormal node.

[0044] By adopting the above technical solution, the computing environment of the abnormal node is synchronized to the pre-configured corresponding backup node based on the computing environment snapshot technology, and an activation instruction is sent to the backup node, so that the backup node is started based on the synchronized computing environment to ensure that it can replace the work of the abnormal node. Based on the task preservation record, the backup node loads the last saved task status on the abnormal node to ensure the normal recovery of the task and its continuation.

[0045] The second object of the invention is achieved by the following technical solutions:

[0046] A sensitive data security association analysis device based on secure multi-party computing, comprising:

[0047] The role creation module is used to create several roles through role definition strategies and grant them corresponding permissions;

[0048] Authentication management module, used to implement identity authentication and authorization management between participants based on communication certificates and key pairs;

[0049] A communication establishment module is used to establish a secure communication tunnel for the participants who have successfully authenticated their identities and used as an encrypted channel for data transmission when the authentication between the participants is successful;

[0050] The data processing module is used to encrypt the sensitive data of the participants and, based on the preset correlation decryption strategy, only partially decrypt the associated data in the predefined calculation process;

[0051] The audit tracking module is used to deploy an audit tracking system to capture and record data access and processing behaviors, and generate an audit log that cannot be tampered with.

[0052] By adopting the above technical solution, a role creation module is used to create several roles through role definition strategies and grant them corresponding permissions; an authentication management module is used to realize identity authentication and authorization management between participants based on communication certificates and key pairs; a communication establishment module is used to establish a secure communication tunnel for data transmission encryption channels for participants who have successfully authenticated their identities when the identity authentication between the participants is successful; a data processing module is used to encrypt the sensitive data of the participants, and based on a preset correlation decryption strategy, only partially decrypt its associated data during a predefined calculation process; an audit tracking module is used to deploy an audit tracking system to capture and record data access and processing behaviors, and generate an audit log that cannot be tampered with.

[0053] In summary, the present application includes at least one of the following beneficial technical effects:

[0054] 1. This application establishes a secure communication tunnel for each participant in the data association analysis after successful identity authentication, encrypts the sensitive data of each participant, and partially decrypts the necessary data only in the predefined necessary calculation process. At the same time, the audit tracking system is used to capture and record the access and processing behavior of the data, thereby protecting the privacy of each party when multiple parties conduct data association analysis, preventing the leakage of sensitive data, and thus improving the security of sensitive data association analysis;

[0055] 2. This application deploys an associative decryption strategy to partially decrypt only the data associated with the identified predefined calculation steps, thereby decrypting the data to a minimum extent and maintaining the calculation steps, which has the effect of improving the security of sensitive data protection;

[0056] 3. This application monitors the computing nodes, and when an abnormal vector is identified, the computing node associated with the abnormal vector is marked as an abnormal node, and the corresponding backup node is activated at the same time, and the computing environment and task status of the abnormal node are synchronized to the backup node. After the backup node is started, all sensitive data of the abnormal node is obtained and encrypted to ensure its security during transmission and storage. The backup node replaces the abnormal node based on a flexible system protocol. When a computing node abnormality is detected, the node is replaced and the data is recovered quickly, which has the effect of improving the security of data processing and ensuring data integrity. The erasure code technology is used to encode the tasks and data being processed to obtain redundant data blocks, thereby improving the fault tolerance and reliability of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 This is a flow chart of an embodiment of a method for secure association analysis of sensitive data based on secure multi-party computing of the present application;

[0058] Figure 2 This is a flowchart for implementing step S30 in an embodiment of a method for secure association analysis of sensitive data based on secure multi-party computing of the present application;

[0059] Figure 3 This is a flowchart for implementing step S40 in an embodiment of a method for secure association analysis of sensitive data based on secure multi-party computing of the present application;

[0060] Figure 4 This is an implementation flow chart after step S40 in an embodiment of a method for secure association analysis of sensitive data based on secure multi-party computing of the present application;

[0061] Figure 5 This is a flowchart for implementing step S420 in an embodiment of a method for secure association analysis of sensitive data based on secure multi-party computing of the present application;

[0062] Figure 6 This is an implementation flowchart of step S430 in an embodiment of a method for secure association analysis of sensitive data based on secure multi-party computing in the present application. DETAILED DESCRIPTION

[0063] The following is combined with Figure 1-6 This application is described in further detail.

[0064] In one embodiment, if Figure 1 As shown, the present application discloses a method for sensitive data security association analysis based on secure multi-party computing, which specifically includes the following steps:

[0065] S10: Create several roles through role definition strategy and grant them corresponding permissions;

[0066] In this embodiment, the role definition strategy is a rule strategy for defining, identifying, assigning, and managing permissions for roles; a role is an entity or user type with a set of specific permissions, responsibilities, and functions;

[0067] Specifically, a number of different roles and corresponding permission lists are created through the role definition strategy, and a permission allocation algorithm is used to grant each role the corresponding minimum and necessary permissions according to the role definition.

[0068] S20: Implement identity authentication and authorization management between participants based on communication certificates and key pairs;

[0069] In this embodiment, the communication certificate is an electronic document used to prove the identity and authority of the holder in network communication, which includes the identity information, public key, signature of the certificate issuing authority and other information of the holder, and is used to verify the identity of the holder and establish a secure communication connection during the communication process; the key pair is an encryption tool consisting of a public key and a private key; the participants are the entities or organizations that participate in the security association analysis of sensitive data in the cloud computing network environment, that is, the entities that need to share, process or analyze sensitive data; identity authentication is the authentication process of confirming the identity and authority of the participants in the network system; authorization management refers to the management process of managing and controlling the authority of the participants to access resources and perform operations in the system;

[0070] Specifically, the participants are required to authenticate each other's identities and perform authorization management on the participants, thereby ensuring that the identities of the participants are authentic and that their operations are in compliance with their granted permissions.

[0071] S30: When the identity authentication between the participants is successful, a secure communication tunnel for data transmission encryption is established for the participants whose identity authentication is successful;

[0072] In this embodiment, an encrypted channel is a transmission path that uses encryption technology to protect data security during communication; a secure communication tunnel is a communication path used to transmit data between two or more participants in a cloud computing network;

[0073] Specifically, when the identity authentication between the participants is successful, a secure communication tunnel for an encrypted channel for data transmission is established between the participants whose identity authentication has been successful, so as to realize secure encrypted communication and data transmission between the participants.

[0074] S40: Encrypt the sensitive data of the participants, and based on a preset correlation decryption strategy, only partially decrypt the associated data in a predefined calculation process;

[0075] In this embodiment, sensitive data refers to information including personal information, financial information, commercial confidential information, medical record information, genomic information, intellectual property information, etc., the disclosure or improper use of which may cause damage to individuals, organizations or systems; the association decryption strategy is a rule strategy based on a specific step and only decrypts data associated with the step; the predefined calculation process is a specific calculation step preset in the association decryption strategy; partial decryption decrypts a part or some parts of the encrypted data, rather than completely decrypting the entire data;

[0076] Specifically, the data of the participants is encrypted to protect their data privacy. At the same time, it is allowed to partially decrypt only the required data based on the preset correlation decryption strategy during the predefined calculation process, so as to meet specific analysis needs.

[0077] S50: Deploy an audit tracking system to capture and record data access and processing behaviors, and generate an audit log that cannot be tampered with;

[0078] In this embodiment, the audit tracking system is a system used to record, track and review data access and data processing behaviors in the system; capture records are the audit tracking system using technical means to record data access behaviors and data processing behaviors; and the unalterable audit log is a log record that cannot be modified or deleted after the content is generated;

[0079] Specifically, an audit tracking system is deployed to capture and record data access and data processing behaviors in the system, so as to record the time, content, implementation subject and other operation behavior information, and generate an unalterable audit log to record and save the operation behavior information;

[0080] Furthermore, based on the anomaly detection system combined with machine learning technology, an alarm is promptly issued when abnormal data access and data processing behaviors are identified, and the abnormal behaviors are responded to and processed.

[0081] In one embodiment, step S20 includes the following steps:

[0082] S201: Obtain the communication certificate of each participant and verify its validity to perform identity authentication;

[0083] S202: Matching corresponding roles for each participant based on the identity information in the communication certificate, thereby implementing authorization management of the participant;

[0084] In this embodiment, verifying the validity of the communication certificate is to check and verify whether the communication certificate is currently valid, whether it is issued by a trusted certificate authority, whether it has not been revoked or expired, etc.;

[0085] Specifically, obtain the communication certificate of each participant, and verify its validity by checking whether the communication certificate is expired, verifying the signature, verifying the domain name, etc. After completing the identity authentication, match the corresponding role for the participant based on the identity information in the communication certificate, thereby granting it the corresponding authority to complete the authorization management.

[0086] In one embodiment, if Figure 2 As shown, step S30 includes the steps of:

[0087] S301: When the identity authentication between the participants is successful, the participants exchange public key certificates;

[0088] S302: Based on the public key certificates obtained by each participant, each participant generates a shared key through a key exchange protocol;

[0089] S303: enabling each participant to obtain a session key for encrypting all communication data in the session based on the shared key;

[0090] In this embodiment, the public key certificate is a digital signature certificate that verifies the legitimacy and security of the public key, thereby ensuring the security of communications; the key exchange protocol is a protocol in which the parties in network communications exchange keys in a secure manner to ensure the security and confidentiality of data during the communication process, which is usually used to establish a shared encryption key between the parties for subsequent data encryption and decryption; the shared key is a key that is jointly held by the parties and used to encrypt and decrypt data; the session key is a dynamically generated key used to encrypt all communication data in a session to ensure the security of data transmission;

[0091] Specifically, when the identity authentication between the participants is successful, the participants exchange their public key certificates and generate a shared key through the key exchange protocol based on the obtained public key certificates as the basis for subsequent encrypted communications. Based on the shared key, each participant obtains a session key used to encrypt all communication data in the session, and uses the session key to enable each participant to establish a secure communication tunnel for an encrypted data transmission channel.

[0092] In one embodiment, if Figure 3 As shown, step S40 includes the steps of:

[0093] S401: Encrypt the sensitive data of all participants based on homomorphic encryption technology to obtain an encrypted data set;

[0094] S402: Based on the pre-deployed correlation decryption strategy, the calculation steps in the calculation process are identified in real time;

[0095] S403: When a predefined calculation step is identified, partially decrypt the data associated with the calculation step;

[0096] In this embodiment, data encrypted by homomorphic encryption technology allows specific computing operations to be performed without decryption, and the result of the computing operation is the same as the result of performing the same operation on the original data after decryption; the encrypted data set is a data set after the data of all participants are encrypted by homomorphic encryption technology; the computing step is a logical operation step when performing a computing task; the predefined computing step is a specific computing step preset in the associative decryption strategy; partially decrypting the data associated with the computing step is partially decrypting the data required in the computing step;

[0097] Specifically, the data of all participants are encrypted using homomorphic encryption technology to obtain an encrypted data set. At the same time, the encrypted data set encrypted by the homomorphic encryption technology allows certain computing operations to be performed without decryption. Based on the pre-deployed associative decryption strategy, the computing process is monitored and identified in real time. When a predefined computing step is identified, the data associated with the step is partially decrypted for the current computing step. The present application deploys an associative decryption strategy to partially decrypt only the data associated with the identified predefined computing step, thereby decrypting the data to a minimum and keeping the computing step in progress, which has the effect of improving the security of sensitive data protection.

[0098] Furthermore, anonymization strategies are used to remove or obfuscate relevant information associated with personal identities in the original data;

[0099] Specifically, anonymization strategies include replacement, generalization, etc.

[0100] Among them, replacement means replacing sensitive data with other non-sensitive data or placeholders, such as replacing a personal name with "User A", etc., and generalization means replacing specific data values ​​with broader categories, such as replacing specific age values ​​with age groups, etc.

[0101] In one embodiment, if Figure 4 As shown, after step S40, the following steps are performed:

[0102] S410: Monitor the computing nodes based on a preset monitoring mechanism, collect performance parameter information of the computing nodes in real time, and record and update historical trend information;

[0103] S420: When it is identified that the performance parameter information contains an abnormal vector, the computing node associated with the abnormal vector is set as an abnormal node;

[0104] S430: Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node, send an activation instruction to the backup node, and load the task status of the abnormal node;

[0105] S440: After the backup node is started, all sensitive data of the abnormal node is obtained, and the obtained sensitive data is encrypted;

[0106] S450: Encode the task and data being processed based on the erasure coding technology to obtain redundant data blocks;

[0107] S460: Based on the elastic system protocol, the backup node replaces the abnormal node and updates the system configuration;

[0108] In this embodiment, the computing node is a node that performs computing tasks; the performance parameter information is a data parameter that describes the performance of the computing node, and is preset to include CPU usage, memory occupancy, disk I / 0 speed, network bandwidth, etc.; the historical trend information is the historical trend of the performance parameter information, that is, the change trend of each parameter when the computing node processes computing steps and tasks; the abnormal vector is a performance parameter value that deviates from normal behavior or performance benchmark; the abnormal node is a computing node that has abnormal performance with an abnormal vector; the backup node is a pre-configured computing node that takes over its work when the main node is abnormal; the activation instruction is an electrical signal instruction for activating the corresponding backup node; the erasure coding technology is a data protection technology that divides data into multiple fragments to restore the original data through the remaining fragments and redundant information when data is lost; the redundant data block is a data copy or redundant data that increases the redundancy of the data obtained by encoding the tasks and data being processed with the erasure coding technology; the elastic system protocol is a protocol that can automatically adapt to the load changes, abnormalities or expansion requirements of the system, which allows the system to dynamically adjust resource allocation, task scheduling and system configuration according to the current situation; the system configuration is the parameters and settings that define the system operation and interaction mode;

[0109] Specifically, during the calculation process, the computing nodes are monitored based on a preset monitoring mechanism, the performance parameter information of the computing nodes is collected in real time, and the historical trend information is recorded and updated. When an abnormal vector is identified, the computing node associated with the abnormal vector is set as an abnormal node, the computing environment of the abnormal node is synchronized to the pre-configured corresponding backup node, and the backup node is activated, the task status of the abnormal node is loaded, and after the backup node is started, all sensitive data of the abnormal node is obtained and decrypted, and the tasks and data being processed are encoded based on the erasure code technology to obtain redundant data blocks, and a flexible system protocol is given to enable the backup node to replace the abnormal node and update the system configuration; this application is implemented by The computing nodes are monitored, and when an abnormal vector is identified, the computing node associated with the abnormal vector is marked as an abnormal node. At the same time, the corresponding backup node is activated, and the computing environment and task status of the abnormal node are synchronized to the backup node. After the backup node is started, all sensitive data of the abnormal node is obtained and encrypted to ensure its security during transmission and storage. Based on the elastic system protocol, the backup node replaces the abnormal node. When the computing node abnormality is detected, the node is quickly replaced and the data is restored, which has the effect of improving the security of data processing and ensuring data integrity. The erasure code technology is used to encode the tasks and data in processing to obtain redundant data blocks, thereby improving the fault tolerance and reliability of the data.

[0110] Further, sensitive data is classified to obtain its sensitivity level, thereby determining the priority and necessity of data encryption based on the sensitivity level;

[0111] Specifically, classify sensitive data to obtain its sensitivity level, for example, determine whether sensitive data is state secrets, commercial secrets or personal privacy; or adopt data classification standards to classify sensitive data into public level, internal level, secret level and confidential level;

[0112] Furthermore, the corresponding security policies are used to determine the integrity requirements of sensitive data through the obtained sensitive data classification information. For example, for confidential sensitive data, high-intensity integrity protection measures are used to ensure that sensitive data is not tampered with, deleted or lost without authorization.

[0113] Among them, high-intensity decryption algorithms, such as AES encryption algorithms, are used for highly sensitive data to improve the level of data protection;

[0114] Furthermore, by evaluating the integrity protection measures for sensitive data, we can obtain the availability requirements for sensitive data. For example, if certain sensitive data needs to be quickly accessible at any time, a more efficient backup and recovery solution can be used to meet this requirement.

[0115] Furthermore, based on the availability requirements of sensitive data, the appropriate storage solution should be selected to determine the storage location of sensitive data: if sensitive data needs to be frequently accessed across borders, it is necessary to consider using cloud storage services and ensure compliance with the data transmission and storage regulations of relevant countries;

[0116] Furthermore, by analyzing sensitive data storage solutions, we can obtain the lifecycle management strategy for sensitive data, for example, determine the protection requirements for sensitive data at each stage from generation, use to archiving, and ensure the security of sensitive data throughout its entire lifecycle;

[0117] Furthermore, through the sensitive data lifecycle management strategy, the access control needs of sensitive data at each stage can be determined, thereby determining the user roles of sensitive data, for example, defining which users or user groups can access specific types of sensitive data and setting corresponding permissions;

[0118] Further, based on the type of computing task or computing step, the encryption strategy is adjusted and the encryption parameters are optimized;

[0119] Among them, if the type of computing task or computing step is designed for high-speed data processing, the grouping mode is adjusted to GCM to optimize the speed and security of the encryption process;

[0120] Furthermore, based on the obtained performance parameter information of the computing node, it is determined whether the computing node is suitable for applying real-time encryption processing. If its computing power allows, a dynamic key management system is adopted to regularly update the key to reduce the risk of the key being cracked.

[0121] In one embodiment, if Figure 5 As shown, step S420 includes the steps of:

[0122] S421: When any parameter in the performance parameter information is lower than or higher than a corresponding preset threshold, the parameter is identified as an abnormal vector;

[0123] S422: Recording the monitoring occurrence time and response interval of the abnormal vector;

[0124] S423: Identify the identity information of the computing node associated with the abnormal vector, and set the computing node as an abnormal node;

[0125] In this embodiment, the monitoring occurrence time is the specific time point when the abnormal vector is monitored and identified; the response interval time is the time interval between when the abnormal vector is identified and when the system or administrator takes corresponding measures;

[0126] Specifically, when any parameter in the performance parameter information is lower than or higher than the corresponding preset threshold, the parameter is identified as an abnormal vector, and the time point when the abnormal vector is identified and the interval time for the system or administrator to take corresponding measures are recorded to analyze the cause of the abnormality and take corresponding countermeasures, identify the identity information of the computing node of the abnormal vector and mark the computing node as an abnormal node.

[0127] In one embodiment, if Figure 6 As shown, step S430 includes the steps of:

[0128] S431: Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node based on the computing environment snapshot technology;

[0129] S432: Sending an activation instruction to the backup node, so that the backup node starts based on the synchronized computing environment;

[0130] S433: Based on the task saving record, load the last saved task status on the abnormal node;

[0131] In this embodiment, the computing environment snapshot technology is a technology that allows the complete state of the system configuration, system data, operating status, etc. at a certain point in time to be quickly captured and saved without affecting the current running system, and is used to quickly restore the system state in the event of a system crash, data loss or other emergency situations; the task save record is the saved information of the task state in the system, which is preset to include task progress, data status, execution time, etc.;

[0132] Specifically, based on the computing environment snapshot technology, the computing environment of the abnormal node is synchronized to the pre-configured corresponding backup node, and an activation instruction is sent to the backup node, so that the backup node is started based on the synchronized computing environment to ensure that it can replace the work of the abnormal node. Based on the task saving record, the backup node loads the last saved task status on the abnormal node to ensure that the task is normally restored and can continue;

[0133] Furthermore, the list of backup nodes is obtained through the consensus algorithm results, and the closest optimal computing node is selected as the backup node based on the performance parameter information.

[0134] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0135] In one embodiment, a device for security association analysis of sensitive data based on secure multi-party computing is provided, and the device for security association analysis of sensitive data based on secure multi-party computing corresponds one-to-one to a method for security association analysis of sensitive data based on secure multi-party computing in the above-mentioned embodiment.

[0136] A sensitive data security association analysis device based on secure multi-party computing, comprising:

[0137] The role creation module is used to create several roles through role definition strategies and grant them corresponding permissions;

[0138] Authentication management module, used to implement identity authentication and authorization management between participants based on communication certificates and key pairs;

[0139] A communication establishment module is used to establish a secure communication tunnel for the participants who have successfully authenticated their identities and used as an encrypted channel for data transmission when the authentication between the participants is successful;

[0140] The data processing module is used to encrypt the sensitive data of the participants and, based on the preset correlation decryption strategy, only partially decrypt the associated data in the predefined calculation process;

[0141] Audit tracking module, which is used to deploy an audit tracking system to capture and record data access and processing behaviors, and generate audit logs that cannot be tampered with;

[0142] Optionally, the authentication management module includes:

[0143] The identity authentication submodule is used to obtain the communication certificate of each participant and verify its validity for identity authentication;

[0144] The authorization management submodule is used to match the corresponding role for each participant based on the identity information in the communication certificate, thereby realizing authorization management of the participants;

[0145] Optionally, the communication establishment module includes:

[0146] The public key exchange submodule is used to exchange public key certificates between the participating parties when the identity authentication between the participating parties is successful;

[0147] A shared key generation submodule is used to enable each participant to generate a shared key through a key exchange protocol based on the public key certificates obtained by each participant;

[0148] A session key acquisition submodule, used to enable each participant to obtain a session key for encrypting all communication data in the session based on the shared key;

[0149] Optionally, the data processing module includes:

[0150] The encryption submodule is used to encrypt the sensitive data of all participants based on homomorphic encryption technology to obtain an encrypted data set;

[0151] The identification submodule is used to identify the calculation steps in the calculation process in real time based on the pre-deployed correlation decryption strategy;

[0152] A decryption submodule, for partially decrypting data associated with a predefined calculation step when the predefined calculation step is identified;

[0153] Optionally, also include:

[0154] The monitoring module is used to monitor the computing nodes based on the preset monitoring mechanism, collect the performance parameter information of the computing nodes in real time, and record and update the historical trend information;

[0155] The abnormality identification module is used to set the computing node associated with the abnormal vector as an abnormal node when the performance parameter information is identified to contain an abnormal vector;

[0156] A synchronous loading module is used to synchronize the computing environment of the abnormal node to the corresponding pre-configured backup node, send an activation instruction to the backup node, and load the task status of the abnormal node;

[0157] The encryption module is used to obtain all sensitive data of the abnormal node after the backup node is started, and encrypt the obtained sensitive data;

[0158] An encoding module, used for encoding the tasks and data being processed based on the erasure coding technology to obtain redundant data blocks;

[0159] A node replacement module is used to enable backup nodes to replace abnormal nodes and update system configuration based on a flexible system protocol;

[0160] Optionally, the anomaly identification module includes:

[0161] The abnormal vector identification submodule is used to identify any parameter in the performance parameter information as an abnormal vector when the parameter is lower than or higher than the corresponding preset threshold value;

[0162] The exception recording submodule is used to record the monitoring occurrence time and response interval time of the exception vector;

[0163] The abnormal node identification submodule is used to identify the identity information of the computing node associated with the abnormal vector and set the computing node as an abnormal node;

[0164] Optionally, synchronously load modules including:

[0165] A computing environment synchronization submodule is used to synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node based on the computing environment snapshot technology;

[0166] An activation submodule, used for sending an activation instruction to the backup node, so that the backup node starts based on the synchronized computing environment;

[0167] The task loading submodule is used to load the last saved task status on the abnormal node based on the task saving record.

[0168] For the specific definition of a sensitive data security association analysis device based on secure multi-party computing, please refer to the definition of a sensitive data security association analysis method based on secure multi-party computing above, which will not be repeated here. Each module in the above-mentioned sensitive data security association analysis device based on secure multi-party computing can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0169] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for sensitive data security association analysis based on secure multi-party computing, characterized in that: Includes steps: Create several roles through role definition strategy and grant them corresponding permissions; Realize identity authentication and authorization management between participants based on communication certificates and key pairs; When the identity authentication between the participants is successful, a secure communication tunnel for data transmission encryption channel is established for the participants with successful identity authentication; Encrypt the sensitive data of the participants, and based on the preset correlation decryption strategy, only partially decrypt the associated data in the predefined calculation process; Deploy an audit tracking system to capture and record data access and processing behaviors, and generate an audit log that cannot be tampered with.

2. The method for sensitive data security association analysis based on secure multi-party computing according to claim 1, characterized in that: The steps of implementing identity authentication and authorization management between participants based on communication certificates and key pairs include the following steps: Obtain the communication certificate of each participant and verify its validity for identity authentication; Based on the identity information in the communication certificate, the corresponding role is matched for each participant, thereby realizing the authorization management of the participants.

3. The method for sensitive data security association analysis based on secure multi-party computing according to claim 1, characterized in that: When the identity authentication between the participants is successful, the step of establishing a secure communication tunnel for the participants who have successfully authenticated their identities for the encrypted data transmission channel comprises the following steps: When the identity authentication between the participants is successful, the public key certificates are exchanged between the participants; Based on the public key certificates obtained by each participant, each participant generates a shared key through a key exchange protocol; Based on the shared key, each participant obtains a session key used to encrypt all communication data in the session.

4. The method for sensitive data security association analysis based on secure multi-party computing according to claim 1, characterized in that: The step of encrypting the sensitive data of the participants and partially decrypting only the associated data in a predefined calculation process based on a preset association decryption strategy comprises the following steps: Encrypt the sensitive data of all participants based on homomorphic encryption technology to obtain an encrypted data set; Based on the pre-deployed correlation decryption strategy, the calculation steps in the calculation process are identified in real time; When a predefined calculation step is identified, the data associated with the calculation step is partially decrypted.

5. The method for sensitive data security association analysis based on secure multi-party computing according to claim 1, characterized in that: After the step of encrypting the sensitive data of the participants and partially decrypting only the associated data in the predefined calculation process based on the preset association decryption strategy, the following steps are performed: Monitor computing nodes based on a preset monitoring mechanism, collect performance parameter information of computing nodes in real time, and record and update historical trend information; When it is identified that the performance parameter information contains an abnormal vector, the computing node associated with the abnormal vector is set as an abnormal node; Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node, send an activation instruction to the backup node, and load the task status of the abnormal node; After the backup node is started, it obtains all sensitive data from the abnormal node and encrypts the obtained sensitive data; Encode the tasks and data being processed based on erasure coding technology to obtain redundant data blocks; The elasticity-based system protocol enables backup nodes to replace abnormal nodes and update the system configuration.

6. The method for sensitive data security association analysis based on secure multi-party computing according to claim 5 is characterized in that: The step of setting the computing node associated with the abnormal vector as an abnormal node when the performance parameter information is identified to contain the abnormal vector comprises the steps of: When any parameter in the performance parameter information is lower than or higher than a corresponding preset threshold, the parameter is identified as an abnormal vector; Record the monitoring occurrence time and response interval of the abnormal vector; The identity information of the computing node associated with the abnormal vector is identified, and the computing node is set as an abnormal node.

7. The method for sensitive data security association analysis based on secure multi-party computing according to claim 5 is characterized in that: The step of synchronizing the computing environment of the abnormal node to a pre-configured corresponding backup node, sending an activation instruction to the backup node, and loading the task status of the abnormal node comprises the following steps: Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node based on the computing environment snapshot technology; Sending an activation instruction to the backup node so that the backup node starts based on the synchronized computing environment; Based on the task save record, load the last saved task status on the abnormal node.

8. A device for sensitive data security association analysis based on secure multi-party computing, characterized in that: include: The role creation module is used to create several roles through role definition strategies and grant them corresponding permissions; Authentication management module, used to implement identity authentication and authorization management between participants based on communication certificates and key pairs; A communication establishment module is used to establish a secure communication tunnel for the participants who have successfully authenticated their identities and used as an encrypted channel for data transmission when the authentication between the participants is successful; The data processing module is used to encrypt the sensitive data of the participants and, based on the preset correlation decryption strategy, only partially decrypt the associated data in the predefined calculation process; The audit tracking module is used to deploy an audit tracking system to capture and record data access and processing behaviors, and generate an audit log that cannot be tampered with.

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