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

Abstract

The present application relates to a method and apparatus for secure association analysis of sensitive data based on secure multi-party computing, comprising the steps of: creating several roles and granting permissions; implementing identity authentication and authorization management between participants; establishing a secure communication tunnel for the participants; encrypting the sensitive data of the participants, and partially decrypting the data only during predefined computing processes; and capturing and recording data access and processing behaviors. The present application establishes a secure communication tunnel for each participant in data association analysis after successful identity authentication, encrypts the sensitive data of each participant, and partially decrypts the necessary data only during predefined required computing processes. At the same time, an audit tracking system is used to capture and record data access and processing behaviors. This protects the privacy of each party when multiple parties conduct data association analysis, prevents the leakage of sensitive data, and improves the security of sensitive data association analysis.

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 and information are becoming increasingly important. Correlation analysis based on sensitive data is playing a crucial role in various industries, such as genetic disease research and satellite trajectory measurement. However, since this data may contain highly confidential personal or corporate information, if leaked, it could be exploited maliciously. Therefore, strict security measures must be implemented when processing and utilizing this 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, this application provides a sensitive data security association analysis method and device based on secure multi-party computing.

[0005] The above-mentioned invention objective of this 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 and grant them corresponding permissions through role definition strategies;

[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 during the predefined calculation process;

[0011] Deploy an audit tracking system to capture and record data access and processing behaviors, and generate tamper-proof audit logs.

[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 allowed to authenticate each other's identities and perform authorization management on the participants, thereby ensuring that the identities of the participants are authentic and reliable, and that their operations comply with their granted permissions; 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 tamper-proof audit logs 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, thereby protecting the privacy of all parties when multiple parties conduct data association analysis, preventing the leakage of sensitive data, and thus improving the security of sensitive data association analysis.

[0013] In a preferred example, the present application may be further configured as follows: the steps of implementing identity authentication and authorization management between participants based on the communication certificate and key pair 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 who have successfully authenticated their identities for the encrypted data transmission channel 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, each participant exchanges its public key certificate and generates a shared key through a key exchange protocol based on the obtained public key certificate, which serves as the basis for subsequent encrypted communication. 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, based on a preset correlation decryption strategy, partially decrypting only the associated data during a predefined calculation process 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 steps, 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 encrypting the sensitive data of the participant and partially decrypting only the associated data in a predefined calculation process based on a preset correlation decryption strategy, the following steps may be 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. 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 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 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. Based on the elastic system protocol, the backup node replaces the abnormal node. When a computing node abnormality is detected, the node is quickly replaced and the data is recovered, 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 includes the following steps:

[0036] 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;

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

[0038] Identify the identity information of the computing node associated with the abnormal vector, and set the computing node 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 of the abnormal vector are recorded to facilitate analysis of its 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 accurate, efficient and reliable processing of abnormal vectors in the performance parameter information.

[0040] In a preferred example, the present application may be further configured as follows: the steps 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 include the following steps:

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

[0042] Sending an activation instruction to the backup node to enable the backup node to start 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 the ability to continue.

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

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

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

[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 authenticated parties when the authentication between the parties 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 during 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 tamper-proof audit logs.

[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 at the same time generate an audit log that cannot be tampered with.

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

[0054] 1. This application establishes a secure communication tunnel for each participant in data correlation analysis after successful identity authentication, encrypts each participant's sensitive data, and partially decrypts necessary data only during predefined, required computations. An audit tracking system is also used to capture and record data access and processing. This protects the privacy of all parties involved in data correlation analysis, prevents the leakage of sensitive data, and thus improves the security of sensitive data correlation analysis.

[0055] 2. This application deploys an associative decryption strategy to partially decrypt only the data associated with the identified predefined computational steps, thereby minimizing the decryption of the data and maintaining the computational steps, thereby improving the security of sensitive data protection.

[0056] 3. This application monitors the computing nodes and marks the computing nodes associated with the abnormal vector as abnormal nodes when an abnormal vector is identified. 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 a 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 applied to encode the tasks and data in processing 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 in 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 flowchart 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, this 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 policy is a rule policy 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 role definition strategies, and a permission allocation algorithm is used to grant each role the corresponding minimum and necessary permissions based on the role definition.

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

[0069] In this embodiment, a communication certificate is an electronic document used to prove the holder's identity and authority in network communications. It includes information such as the holder's identity information, public key, and the signature of the certificate authority, and is used to verify the holder's identity and establish a secure communication connection during the communication process. A key pair is an encryption tool consisting of a public key and a private key. Participants are entities or organizations that participate in the security association analysis of sensitive data in a cloud computing network environment, that is, entities that need to share, process, or analyze sensitive data. Identity authentication is the authentication process of confirming the identity and authority of participants in the network system. Authorization management refers to the management process of managing and controlling the rights of 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 reliable, 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 identities have been successfully authenticated;

[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 is 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 during a predefined calculation process;

[0075] In this embodiment, sensitive data refers to information including personal information, financial information, commercial confidential information, medical records, genomic information, intellectual property information, etc., the disclosure or improper use of which may cause damage to individuals, organizations, or systems; a correlation decryption strategy is a rule-based strategy based on a specific step and only decrypts data associated with that step; a predefined calculation process is a specific calculation step preset in the correlation decryption strategy; partial decryption decrypts a portion or 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 allows only partial decryption of the required data based on the preset correlation decryption strategy during the predefined calculation process, thereby meeting specific analysis needs.

[0077] S50: Deploy an audit tracking system to capture and record data access and processing behaviors, and generate an unalterable audit log.

[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 and data processing behaviors; and unalterable audit logs are log records whose content cannot be modified or deleted after being generated.

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

[0080] Furthermore, an anomaly detection system based on machine learning technology can promptly issue an alarm when abnormal data access and data processing behaviors are identified, and respond to the abnormal behaviors.

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

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

[0083] S202: Based on the identity information in the communication certificate, the corresponding role is matched for each participant, 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, and whether it has not been revoked or expired;

[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 and completing the authorization management.

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

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

[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: Based on the shared key, each participant obtains a session key for encrypting all communication data in the session;

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

[0091] Specifically, when the identity authentication between the participants is successful, each participant exchanges its public key certificate and generates a shared key through the key exchange protocol based on the obtained public key certificate as the basis for subsequent encrypted communication. Each participant obtains a session key for encrypting all communication data in the session based on the shared key, and uses the session key to enable each participant to establish a secure communication tunnel for data transmission encryption channel.

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

[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 using 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 the data set after the data of all participants are encrypted using homomorphic encryption technology; the computing step is the logical operation step when performing a computing task; the predefined computing step is the specific computing step preset in the associative decryption strategy; and partially decrypting the data associated with the computing step is partially decrypting the data required for the computing step.

[0097] Specifically, homomorphic encryption technology is used to encrypt the data of all participants to obtain an encrypted data set. At the same time, the encrypted data set encrypted by 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. This 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 maintaining the computing step, 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, it obtains all sensitive data of the abnormal node and encrypts the obtained sensitive data;

[0106] S450: Encode the task and data being processed based on 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, a computing node is a node that performs computing tasks; performance parameter information is data parameters that describe the performance of the computing node, and preset parameters include CPU usage, memory occupancy, disk I / O speed, network bandwidth, etc.; historical trend information is the historical trend of performance parameter information, that is, the changing trend of each parameter when the computing node processes computing steps and tasks; anomaly vectors are performance parameter values ​​that deviate from normal behavior or performance benchmarks; abnormal nodes are computing nodes that exhibit abnormal behavior due to abnormal vectors; backup nodes are pre-configured computing nodes used to take over the work of the primary node when an abnormality occurs; activation instructions are electrical signal instructions used to activate the corresponding backup node; erasure coding technology is a data protection technology that divides data into multiple fragments so that the original data can be restored through the remaining fragments and redundant information when data is lost; redundant data blocks are data copies or redundant data that increase data redundancy by encoding the tasks and data being processed using erasure coding technology; a flexible system protocol is a protocol that can automatically adapt to system load changes, abnormalities, or expansion requirements, allowing the system to dynamically adjust resource allocation, task scheduling, and system configuration based on the current situation; system configuration is the parameters and settings that define the system's operation and interaction methods;

[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. 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 a 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, improving the fault tolerance and reliability of the data.

[0110] Furthermore, 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, sensitive data can be classified to obtain its sensitivity level, for example, to determine whether sensitive data is state secrets, commercial secrets, or personal privacy; or data classification standards can be used to classify sensitive data into public, internal, secret, and confidential levels;

[0112] Furthermore, the obtained sensitive data classification information is used to adopt corresponding security policies to determine the integrity requirements of sensitive data. For example, for confidential sensitive data, high-intensity integrity protection measures are adopted 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 algorithm, 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 determine the availability requirements for sensitive data. For example, if 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, the storage location of sensitive data should be determined by selecting an appropriate storage solution based on the availability requirements of the sensitive data. If sensitive data needs to be frequently accessed across borders, cloud storage services should be considered, ensuring compliance with the data transfer and storage regulations of the relevant countries.

[0116] Furthermore, by analyzing sensitive data storage solutions, we can obtain a lifecycle management strategy for sensitive data. For example, we can determine the protection requirements for sensitive data at each stage from generation to use to archiving, ensuring 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, it can define which users or user groups can access specific types of sensitive data and set corresponding permissions;

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

[0119] If the type of computing task or computing step requires high-speed data processing, adjust the grouping mode 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 following steps:

[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 is the time interval between the abnormal vector being identified and the system or administrator taking 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 facilitate analysis of the cause of the abnormality and take corresponding countermeasures. The identity information of the computing node of the abnormal vector is identified and the computing node is marked as an abnormal node.

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

[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 save 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 rapid capture and preservation of the complete state of the system configuration, system data, operating status, etc. at a certain point in time without affecting the currently running system. It is used to quickly restore the system state in the event of a system crash, data loss, or other emergency. The task save record is the saved information of the task status in the system, which preset includes task progress, data status, execution time, etc.

[0132] Specifically, the computing environment of the abnormal node is synchronized to the corresponding pre-configured backup node based on computing environment snapshot technology. An activation instruction is sent to the backup node, causing it to start based on the synchronized computing environment to ensure that it can replace the work of the abnormal node. Based on the task storage record, the backup node loads the last saved task status on the abnormal node to ensure normal recovery and continuation of the task.

[0133] Furthermore, the backup node list 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 this application.

[0135] In one embodiment, a device for security association analysis of sensitive data based on secure multi-party computing is provided. 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 embodiment.

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

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

[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 authenticated parties when the authentication between the parties 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 during the predefined calculation process;

[0141] Audit tracking module, used to deploy an audit tracking system to capture and record data access and processing behaviors, and generate tamper-proof audit logs;

[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] The 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, configured 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, configured to partially decrypt 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] an abnormality identification module, configured to, when identifying that the performance parameter information contains an abnormal vector, set the computing node associated with the abnormal vector as an abnormal node;

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

[0159] Node replacement module, used to enable backup nodes to replace abnormal nodes and update system configuration based on elastic system protocols;

[0160] Optionally, the anomaly identification module includes:

[0161] An 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;

[0162] The exception recording submodule is used to record the monitoring occurrence time and response interval 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 loaded modules include:

[0165] The 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, configured to send an activation instruction to the backup node, so that the backup node starts up 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] Regarding the specific definition of a device for secure association analysis of sensitive data based on secure multi-party computing, please refer to the definition of a method for secure association analysis of sensitive data based on secure multi-party computing above, which will not be repeated here. Each module in the above-mentioned device for secure association analysis of sensitive data based on secure multi-party computing can be implemented in whole or in part by software, hardware, and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0169] The above-described embodiments 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, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for sensitive data security association analysis based on secure multi-party computing, characterized in that: Including steps: Create several roles and grant them corresponding permissions through role definition strategies; 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 during the predefined calculation process; 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; 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 includes the following steps: Synchronize the computing environment of the abnormal node to the pre-configured corresponding backup node based on computing environment snapshot technology; Sending an activation instruction to the backup node to enable the backup node to start based on the synchronized computing environment; Based on the task save record, load the last saved task status on 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; Before encrypting sensitive data, the sensitive data is classified to obtain its sensitivity level, and the integrity requirements of the sensitive data are judged based on the classification results and its sensitivity level, combined with the preset corresponding security policy; Based on the integrity requirements of sensitive data, obtain the availability requirements of sensitive data and match the corresponding storage solution; Obtain the lifecycle management strategy for sensitive data based on the storage solution for sensitive data, determine the access control needs at each stage of the lifecycle, and determine the user roles associated with sensitive data and their corresponding permissions; Deploy an audit tracking system to capture and record data access and processing behaviors, and generate tamper-proof audit logs.

2. The method for sensitive data security association analysis based on secure multi-party computation 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 computation 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 and used as an encrypted data transmission channel includes 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 computation 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 correlation decryption strategy includes 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 computation according to claim 1, characterized in that: The step of setting a computing node associated with an abnormal vector as an abnormal node when an abnormal vector is identified in the performance parameter information includes the following steps: 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; Record the monitoring occurrence time and response interval of the abnormal vector; Identify the identity information of the computing node associated with the abnormal vector, and set the computing node as an abnormal node.

6. A device for secure association analysis of sensitive data based on secure multi-party computing, used in the steps of a method for secure association analysis of sensitive data based on secure multi-party computing according to any one of claims 1 to 5, characterized in that: include: The role creation module is used to create several roles and grant them corresponding permissions through role definition strategies; 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 authenticated parties when the authentication between the parties 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 during 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 tamper-proof audit logs.

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