A privacy data processing system based on trusted data space

Abstract

The present invention provides a privacy data processing system based on a trusted data space, which relates to the technical field of privacy processing. The system comprises: when it is monitored that the trusted data space is in a high-load situation, obtaining the privacy data to be processed in the trusted data space, and building a distributed architecture to perform distributed privacy processing on the privacy data to be processed; obtaining the configuration data of the trusted data space, setting an elastic expansion strategy, and performing elastic expansion processing according to processing configuration requirements; setting a privacy processing level, obtaining the data volume distribution and the privacy data volume of the privacy data to be processed, determining the level to be processed, and performing load balancing processing in combination with distributed privacy processing and elastic expansion processing; when the trusted data space is continuously in a high-load situation, optimizing the privacy processing algorithm of the privacy data to be processed; and facilitating efficient processing of privacy data in the trusted data space under high-load conditions.

Description

Technical Field

[0001] The present invention relates to the field of privacy processing technology, and in particular to a privacy data processing system based on a trusted data space. Background Art

[0002] With the rapid development of big data and artificial intelligence technologies, the protection of personal privacy data has become an important issue in the information society. In the process of data processing and analysis, in order to effectively protect data privacy and ensure the authenticity and credibility of data, high load will inevitably occur in the privacy processing process, which will lead to inefficient privacy processing.

[0003] Therefore, the present invention provides a privacy data processing system based on a trusted data space. Summary of the invention

[0004] The present invention provides a privacy data processing system based on a trusted data space. When it is monitored that the trusted data space is in a high-load situation, the privacy data to be processed in the trusted data space is obtained, and a distributed architecture is constructed to perform distributed privacy processing on the privacy data to be processed; the configuration data of the trusted data space is obtained, an elastic expansion strategy is set, and elastic expansion processing is performed on the privacy data to be processed according to the processing configuration requirements of the privacy data to be processed and the configuration data; the privacy processing level is set, the data volume distribution and the privacy data volume of the privacy data to be processed are obtained, the privacy processing level of the privacy data to be processed is determined, and load balancing processing is performed on the privacy data to be processed in combination with distributed privacy processing and elastic expansion processing; when the trusted data space is continuously in a high-load situation, the privacy processing algorithm of the privacy data to be processed is optimized; this is conducive to the efficient processing of privacy data in the trusted data space under high-load conditions.

[0005] The present invention provides a privacy data processing system based on a trusted data space, comprising:

[0006] The distributed architecture module is used to obtain the pending privacy data in the trusted data space when it is detected that the trusted data space is under high load, and to build a distributed architecture to perform distributed privacy processing on the pending privacy data;

[0007] The elastic expansion module is used to obtain the configuration data of the trusted data space, set the elastic expansion strategy, and perform elastic expansion processing on the privacy data to be processed according to the processing configuration requirements and configuration data of the privacy data to be processed;

[0008] The hierarchical load module is used to set the privacy processing level, obtain the data volume distribution and amount of privacy data to be processed, determine the privacy processing level of the privacy data to be processed, and perform load balancing on the privacy data to be processed by combining distributed privacy processing and elastic expansion processing;

[0009] The privacy processing optimization module is used to optimize the privacy processing algorithm of the privacy data to be processed when the trusted data space is continuously under high load.

[0010] According to the present invention, a privacy data processing system based on a trusted data space and a distributed architecture module are provided, comprising:

[0011] A load monitoring unit is used to monitor the load of the trusted data space in real time, obtain a set load threshold, and determine that the trusted data space is in a high load state when the current load threshold of the trusted data space is not lower than the set load threshold;

[0012] When the current load value of the trusted data space is lower than the set load threshold, it is determined that the trusted data space is in a low load state;

[0013] The to-be-processed privacy data unit is used to obtain the to-be-processed privacy data of the trusted data space when it is monitored that the trusted data space is in a high-load situation, wherein the to-be-processed privacy data includes: to-be-processed real privacy data and to-be-processed virtual privacy data;

[0014] A distributed architecture unit is used to obtain the privacy processing requirements and data characteristics of the privacy data to be processed, divide the privacy data to be processed according to the privacy processing requirements and data characteristics, and obtain the privacy sub-data to be processed;

[0015] Obtain the privacy processing nodes of the trusted data space, build a distributed architecture, randomly allocate the privacy sub-data to be processed according to the privacy processing resources of the privacy processing nodes, and perform distributed privacy processing;

[0016] When the privacy processing node completes the distributed privacy processing, the distributed privacy processing results are aggregated and merged.

[0017] According to a privacy data processing system based on a trusted data space provided by the present invention, a load monitoring unit includes:

[0018] The load collection block is used to obtain the load data of the trusted data space from the privacy processing node of the trusted data space in real time according to the preset load indicators, wherein the load indicators include: CPU utilization index, memory utilization index, read and write response efficiency index, network bandwidth utilization index and privacy processing task volume index;

[0019] A load threshold block is used to set the total load threshold of the trusted data space and the node load threshold of the privacy processing node of the trusted data space, and divide the load situation of the trusted data space into a high load situation and a low load situation;

[0020] A load determination block, used to determine that the trusted data space is in a high load condition when the current node load value of the trusted data space is not lower than the node load threshold or the current total space load value is not lower than the total space load threshold;

[0021] When the current node load values ​​of the trusted data space are all lower than the node load threshold and the current space total load value is lower than the space total load threshold, it is determined that the trusted data space is in a low load condition.

[0022] According to a privacy data processing system based on a trusted data space provided by the present invention, a privacy data unit to be processed includes:

[0023] The pending privacy data block is used to obtain the privacy data of the trusted data space when it is monitored that the trusted data space is under high load, and to determine the pending privacy data of the trusted data space according to the total space load threshold and the node load threshold, wherein the privacy data of the trusted data space includes: pending privacy data and processed privacy data.

[0024] According to the present invention, a privacy data processing system based on a trusted data space and an elastic expansion module are provided, comprising:

[0025] A configuration data unit, used to obtain configuration data of the trusted data space, wherein the configuration data includes: resource configuration data, node configuration data, memory capacity configuration data, network bandwidth configuration data, and privacy processing performance configuration data;

[0026] The elastic expansion unit is used to set elastic expansion strategies and obtain the processing configuration requirements of the privacy data to be processed when it is detected that the trusted data space is under high load;

[0027] Get the currently enabled privacy processing nodes and currently disabled privacy processing nodes of the trusted data space, and enable the currently disabled privacy processing nodes or expand the configuration data of the currently enabled privacy processing nodes according to the processing configuration requirements of the privacy data to be processed, the configuration data of the currently enabled privacy processing nodes, and the configuration data of the currently disabled privacy processing nodes, to perform elastic expansion processing on the privacy data to be processed.

[0028] According to the present invention, a privacy data processing system based on a trusted data space and a layered load module are provided, comprising:

[0029] A privacy processing level unit, used to set the privacy processing level of the trusted data space according to the privacy data volume and privacy processing requirements of the private data in the trusted data space, wherein the privacy processing level refers to: a privacy processing layer and a privacy processing level;

[0030] The privacy data to be processed is processed in layers according to the privacy processing layer, and data preprocessing is performed on the privacy basic layer to remove duplicate data in the privacy data to be processed. The privacy processing layer includes: a privacy basic layer, a privacy encryption layer, a privacy comprehensive processing layer, and a privacy aggregation layer;

[0031] Perform data encryption processing on the privacy data to be processed after data preprocessing in the privacy encryption layer;

[0032] In the privacy comprehensive processing layer, the privacy data to be processed after data encryption is processed is load balanced by combining distributed privacy processing and elastic expansion processing;

[0033] Summarize the load balancing processing results at the data aggregation layer;

[0034] Determine the processing order of the privacy data to be processed in the same privacy processing layer according to the privacy processing level;

[0035] A privacy processing node in the trusted data space is randomly selected as the coordinate origin, a coordinate system is established, and the data volume distribution and the amount of privacy data to be processed are obtained according to the privacy data to be processed of the privacy processing node in the trusted data space;

[0036] A load balancing processing unit, used to determine the privacy processing nodes with high load and the privacy processing nodes with low load in the trusted data space according to the data volume distribution of the privacy data to be processed, combined with distributed privacy processing and elastic expansion processing, and obtain the load migration amount of the trusted data space;

[0037] ;in, Indicates the load migration amount of the trusted data space; Indicates At the privacy processing node under high load The data quantification value of the privacy data to be processed; Indicates The privacy processing node in the low load case The data quantification value of processed privacy data; Indicates At the privacy processing node under high load The probability that the private data to be processed is the real private data to be processed; Indicates The amount of privacy data to be processed at the privacy processing node under high load conditions; The number of privacy processing nodes representing high load conditions in the trusted data space; The number of privacy processing nodes representing low load conditions in the trusted data space; Indicates The number of privacy data to be processed at the privacy processing node under high load conditions;

[0038] The processing order of the privacy data to be processed is determined according to the data volume distribution and privacy processing level of the privacy data to be processed, and load balancing is performed on the privacy data to be processed in combination with the load migration amount of the trusted data space.

[0039] A privacy data processing system based on a trusted data space provided by the present invention further includes:

[0040] The privacy processing sequence unit is used to prioritize distributed privacy processing and elastic expansion processing of the privacy data to be processed when it is detected that the trusted data space is under high load;

[0041] If the distributed privacy processing results show that the trusted data space is still handling a high load, load balancing will be performed on the privacy data to be processed.

[0042] According to the present invention, a privacy data processing system based on a trusted data space and a privacy processing optimization module are provided, comprising:

[0043] A privacy processing optimization unit, used to obtain the load status of the trusted data space that has completed load balancing processing of the privacy data to be processed;

[0044] When the load condition of the trusted data space is high, and when it is determined that the trusted data space is continuously in a high load condition, the privacy processing algorithm of the privacy data to be processed is optimized according to the preset privacy processing algorithm, wherein the preset privacy processing algorithm includes: same-station encryption algorithm, secure multi-party computing algorithm and differential privacy computing algorithm.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] When it is monitored that the trusted data space is under high load, the privacy data to be processed in the trusted data space is obtained, and a distributed architecture is constructed to perform distributed privacy processing on the privacy data to be processed; the configuration data of the trusted data space is obtained, and an elastic expansion strategy is set, and elastic expansion processing is performed on the privacy data to be processed according to the processing configuration requirements and configuration data of the privacy data to be processed; the privacy processing level is set, the data volume distribution and the amount of privacy data to be processed are obtained, the privacy processing level of the privacy data to be processed is determined, and the load balancing processing is performed on the privacy data to be processed in combination with distributed privacy processing and elastic expansion processing; when the trusted data space is continuously under high load, the privacy processing algorithm of the privacy data to be processed is optimized; this is conducive to the efficient processing of privacy data in the trusted data space under high load conditions.

[0047] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0048] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0050] Figure 1 It is a structural diagram of a privacy data processing system based on a trusted data space provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0052] Embodiment 1:

[0053] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, such as Figure 1 As shown, including:

[0054] The distributed architecture module is used to obtain the pending privacy data in the trusted data space when it is detected that the trusted data space is under high load, and to build a distributed architecture to perform distributed privacy processing on the pending privacy data;

[0055] The elastic expansion module is used to obtain the configuration data of the trusted data space, set the elastic expansion strategy, and perform elastic expansion processing on the privacy data to be processed according to the processing configuration requirements and configuration data of the privacy data to be processed;

[0056] The hierarchical load module is used to set the privacy processing level, obtain the data volume distribution and amount of privacy data to be processed, determine the privacy processing level of the privacy data to be processed, and perform load balancing on the privacy data to be processed by combining distributed privacy processing and elastic expansion processing;

[0057] The privacy processing optimization module is used to optimize the privacy processing algorithm of the privacy data to be processed when the trusted data space is continuously under high load.

[0058] In this embodiment, the to-be-processed privacy data refers to unprocessed privacy data in the trusted data space when the trusted data space is under a high load condition.

[0059] In this embodiment, the distributed architecture refers to an architecture constructed by the trusted data space based on the privacy processing nodes, which is used to efficiently process privacy data.

[0060] In this embodiment, distributed privacy processing refers to privacy processing performed by randomly allocating privacy sub-data to be processed according to the privacy processing resources of the privacy processing nodes, and is used to perform efficient privacy processing on the privacy data to be processed when processing high load in the trusted data space.

[0061] In this embodiment, the configuration data refers to the data configured by the trusted data space for performing privacy processing on the private data.

[0062] In this embodiment, the elastic expansion strategy refers to a strategy for performing privacy processing on private data through expansion configuration when the trusted data space is under high load.

[0063] In this embodiment, the processing configuration requirement refers to the processing configuration requirement required to achieve efficient privacy processing of the privacy data to be processed under high load conditions.

[0064] In this embodiment, elastic expansion processing refers to performing privacy processing on private data in a trusted data space under high load conditions according to an elastic expansion strategy.

[0065] In this embodiment, the privacy processing level refers to a processing stage and a processing priority for indicating privacy processing of privacy data.

[0066] In this embodiment, data volume distribution refers to the data distribution of the privacy data to be processed in each privacy processing node.

[0067] In this embodiment, the amount of private data refers to the amount of private information contained in the private data to be processed.

[0068] In this embodiment, load balancing processing refers to privacy processing performed on the privacy data to be processed according to the privacy processing level, distributed privacy processing, and elastic expansion processing.

[0069] In this embodiment, the privacy processing algorithm refers to an algorithm used by the trusted data space to perform privacy processing on private data.

[0070] The working principle and beneficial effects of the above technical solution are: when it is monitored that the trusted data space is in a high-load situation, the privacy data to be processed in the trusted data space is obtained, and a distributed architecture is constructed to perform distributed privacy processing on the privacy data to be processed; the configuration data of the trusted data space is obtained, and an elastic expansion strategy is set, and elastic expansion processing is performed on the privacy data to be processed according to the processing configuration requirements of the privacy data to be processed and the configuration data; the privacy processing level is set, the data volume distribution and the privacy data volume of the privacy data to be processed are obtained, the privacy processing level of the privacy data to be processed is determined, and the distributed privacy processing and elastic expansion processing are combined to perform load balancing processing on the privacy data to be processed; when the trusted data space is continuously in a high-load situation, the privacy processing algorithm of the privacy data to be processed is optimized; this is conducive to the efficient processing of privacy data in the trusted data space under high-load conditions.

[0071] Embodiment 2:

[0072] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, a distributed architecture module, including:

[0073] A load monitoring unit is used to monitor the load of the trusted data space in real time, obtain a set load threshold, and determine that the trusted data space is in a high load state when the current load threshold of the trusted data space is not lower than the set load threshold;

[0074] When the current load value of the trusted data space is lower than the set load threshold, it is determined that the trusted data space is in a low load state;

[0075] The to-be-processed privacy data unit is used to obtain the to-be-processed privacy data of the trusted data space when it is monitored that the trusted data space is in a high-load situation, wherein the to-be-processed privacy data includes: to-be-processed real privacy data and to-be-processed virtual privacy data;

[0076] A distributed architecture unit is used to obtain the privacy processing requirements and data characteristics of the privacy data to be processed, divide the privacy data to be processed according to the privacy processing requirements and data characteristics, and obtain the privacy sub-data to be processed;

[0077] Obtain the privacy processing nodes of the trusted data space, build a distributed architecture, randomly allocate the privacy sub-data to be processed according to the privacy processing resources of the privacy processing nodes, and perform distributed privacy processing;

[0078] When the privacy processing node completes the distributed privacy processing, the distributed privacy processing results are aggregated and merged.

[0079] In this embodiment, the trusted data space refers to a space used to perform privacy computing on private data.

[0080] In this embodiment, the load condition of the trusted data space refers to the resource usage of the trusted data space when performing privacy computing on private data, including: a high load condition and a low load condition. The high load condition indicates that the trusted data space has insufficient computing resources when performing privacy computing on private data; the low load condition indicates that the trusted data space has sufficient computing resources when performing privacy computing on private data and can effectively complete the privacy computing.

[0081] In this embodiment, setting the load threshold refers to a threshold used to divide a high load situation and a low load situation.

[0082] In this embodiment, the privacy data to be processed refers to the unprocessed privacy data in the trusted data space when the trusted data space is under a high load condition, including: real privacy data to be processed and virtual privacy data to be processed.

[0083] In this embodiment, the real privacy data to be processed refers to the data that actually has privacy in the privacy data. For example, the spatial data in the privacy data a1 to be processed is set as the real privacy data to be processed; the virtual privacy data to be processed refers to the data that does not have privacy in the privacy data. For example, the time data in the privacy data a1 to be processed is set as the virtual privacy data to be processed.

[0084] In this embodiment, the privacy processing requirement refers to the privacy processing efficiency requirement and the privacy processing quality requirement.

[0085] In this embodiment, the privacy sub-data to be processed refers to the data obtained by dividing the privacy data to be processed according to the privacy processing requirements and data characteristics. For example, the privacy data to be processed with consistent data characteristics and privacy processing requirements are divided into one category of data, which is recorded as the privacy sub-data to be processed.

[0086] In this embodiment, the privacy processing node refers to a node in the trusted data space used to perform privacy calculation and privacy processing on private data.

[0087] In this embodiment, the distributed architecture refers to an architecture constructed by the trusted data space based on the privacy processing nodes, which is used to efficiently process privacy data.

[0088] In this embodiment, the privacy processing resources refer to the resources at the privacy processing node used to perform privacy computing or privacy processing on the privacy data.

[0089] In this embodiment, distributed privacy processing refers to privacy processing performed by randomly allocating privacy sub-data to be processed according to the privacy processing resources of the privacy processing nodes, and is used to perform efficient privacy processing on the privacy data to be processed when processing high load in the trusted data space.

[0090] In this embodiment, the distributed privacy processing results are aggregated and merged to determine the processing effect and processing quality of the distributed privacy processing results.

[0091] The working principle and beneficial effects of the above technical solution are: when it is monitored that the trusted data space is under high load, the pending privacy data of the trusted data space is obtained, and a distributed architecture is constructed to perform distributed privacy processing on the pending privacy data, which is conducive to preliminary privacy processing of the pending privacy data under high load conditions.

[0092] Embodiment 3:

[0093] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, a load monitoring unit, including:

[0094] The load collection block is used to obtain the load data of the trusted data space from the privacy processing node of the trusted data space in real time according to the preset load indicators, wherein the load indicators include: CPU utilization index, memory utilization index, read and write response efficiency index, network bandwidth utilization index and privacy processing task volume index;

[0095] A load threshold block is used to set the total load threshold of the trusted data space and the node load threshold of the privacy processing node of the trusted data space, and divide the load situation of the trusted data space into a high load situation and a low load situation;

[0096] A load determination block, used to determine that the trusted data space is in a high load condition when the current node load value of the trusted data space is not lower than the node load threshold or the current total space load value is not lower than the total space load threshold;

[0097] When the current node load values ​​of the trusted data space are all lower than the node load threshold and the current space total load value is lower than the space total load threshold, it is determined that the trusted data space is in a low load condition.

[0098] In this embodiment, the preset load index refers to an index used to measure the load condition of the trusted data space.

[0099] In this embodiment, load data refers to data used to represent the load status of the trusted data space, such as central processing unit utilization data, memory utilization data, read and write response efficiency data, network bandwidth utilization data, and privacy processing task volume data.

[0100] In this embodiment, the total space load threshold refers to the threshold used to divide the trusted data space into high load conditions and low load conditions. For example, the total space load threshold a1, when the load value a2>a1 of the trusted data space, it is determined that the trusted data space is in a high load condition.

[0101] In this embodiment, the node load threshold refers to the threshold used to divide the privacy processing node in the trusted data space into high load and low load conditions. For example, the node load threshold b1, when the node load value b2>b1 of the privacy processing node, it is determined that the privacy processing node is in a high load condition and the trusted data space is in a high load condition.

[0102] The working principle and beneficial effect of the above technical solution are: by real-time monitoring of the load condition of the trusted data space, the load condition of the trusted data space is determined, laying a foundation for the load condition for subsequent privacy processing of the privacy data.

[0103] Embodiment 4:

[0104] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, wherein the privacy data unit to be processed includes:

[0105] The pending privacy data block is used to obtain the privacy data of the trusted data space when it is monitored that the trusted data space is under high load, and to determine the pending privacy data of the trusted data space according to the total space load threshold and the node load threshold, wherein the privacy data of the trusted data space includes: pending privacy data and processed privacy data.

[0106] In this embodiment, the to-be-processed privacy data refers to unprocessed privacy data in the trusted data space when the trusted data space is under a high load condition.

[0107] In this embodiment, the privacy data to be processed in the trusted data space is determined based on the total space load threshold and the node load threshold. For example, if the current node load value of the privacy processing node a1 is not lower than the node load threshold, the privacy data that is being processed and has been processed at the privacy processing node a1 is recorded as processed privacy data, and the remaining privacy data is recorded as privacy data to be processed.

[0108] The working principle and beneficial effect of the above technical solution are: by obtaining the privacy data of the trusted data space, the privacy data to be processed in the trusted data space is determined, laying a data foundation for subsequent privacy data processing.

[0109] Embodiment 5:

[0110] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, an elastic expansion module, including:

[0111] A configuration data unit, used to obtain configuration data of the trusted data space, wherein the configuration data includes: resource configuration data, node configuration data, memory capacity configuration data, network bandwidth configuration data, and privacy processing performance configuration data;

[0112] The elastic expansion unit is used to set elastic expansion strategies and obtain the processing configuration requirements of the privacy data to be processed when it is detected that the trusted data space is under high load;

[0113] Get the currently enabled privacy processing nodes and currently disabled privacy processing nodes of the trusted data space, and enable the currently disabled privacy processing nodes or expand the configuration data of the currently enabled privacy processing nodes according to the processing configuration requirements of the privacy data to be processed, the configuration data of the currently enabled privacy processing nodes, and the configuration data of the currently disabled privacy processing nodes, to perform elastic expansion processing on the privacy data to be processed.

[0114] In this embodiment, the configuration data of the trusted data space refers to the data configured by the trusted data space for privacy processing of private data, including: resource configuration data, node configuration data, memory capacity configuration data, network bandwidth configuration data and privacy processing performance configuration data.

[0115] In this embodiment, the elastic expansion strategy refers to a strategy for performing privacy processing on private data through expansion configuration when the trusted data space is under high load.

[0116] In this embodiment, the processing configuration requirement refers to the processing configuration requirement required to achieve efficient privacy processing of the privacy data to be processed under high load conditions.

[0117] In this embodiment, the currently enabled privacy processing node refers to the privacy processing node that is enabled when the current trusted data space is under high load; the currently unenabled privacy processing node refers to the privacy processing node that is not enabled when the current trusted data space is under high load.

[0118] The working principle and beneficial effects of the above technical solution are: by obtaining the configuration data of the trusted data space, setting the elastic expansion strategy, elastically expanding the privacy data to be processed according to the processing configuration requirements and configuration data of the privacy data to be processed, and further realizing privacy processing of the privacy data in the trusted data space under high load conditions.

[0119] Embodiment 6:

[0120] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, a layered load module, including:

[0121] A privacy processing level unit, used to set the privacy processing level of the trusted data space according to the privacy data volume and privacy processing requirements of the private data in the trusted data space, wherein the privacy processing level refers to: a privacy processing layer and a privacy processing level;

[0122] The privacy data to be processed is processed in layers according to the privacy processing layer, and data preprocessing is performed on the privacy basic layer to remove duplicate data in the privacy data to be processed. The privacy processing layer includes: a privacy basic layer, a privacy encryption layer, a privacy comprehensive processing layer, and a privacy aggregation layer;

[0123] Perform data encryption processing on the privacy data to be processed after data preprocessing in the privacy encryption layer;

[0124] In the privacy comprehensive processing layer, the privacy data to be processed after data encryption is processed is load balanced by combining distributed privacy processing and elastic expansion processing;

[0125] Summarize the load balancing processing results at the data aggregation layer;

[0126] Determine the processing order of the privacy data to be processed in the same privacy processing layer according to the privacy processing level;

[0127] A privacy processing node in the trusted data space is randomly selected as the coordinate origin, a coordinate system is established, and the data volume distribution and the amount of privacy data to be processed are obtained according to the privacy data to be processed of the privacy processing node in the trusted data space;

[0128] A load balancing processing unit, used to determine the privacy processing nodes with high load and the privacy processing nodes with low load in the trusted data space according to the data volume distribution of the privacy data to be processed, combined with distributed privacy processing and elastic expansion processing, and obtain the load migration amount of the trusted data space;

[0129] ;in, Indicates the load migration amount of the trusted data space; Indicates At the privacy processing node under high load The data quantification value of the privacy data to be processed; Indicates The privacy processing node in the low load case The data quantification value of processed privacy data; Indicates At the privacy processing node under high load The probability that the private data to be processed is the real private data to be processed; Indicates The amount of privacy data to be processed at the privacy processing node under high load conditions; The number of privacy processing nodes representing high load conditions in the trusted data space; The number of privacy processing nodes representing low load conditions in the trusted data space; Indicates The number of privacy data to be processed at the privacy processing node under high load conditions;

[0130] The processing order of the privacy data to be processed is determined according to the data volume distribution and privacy processing level of the privacy data to be processed, and load balancing is performed on the privacy data to be processed in combination with the load migration amount of the trusted data space.

[0131] In this embodiment, the privacy processing level refers to the processing stage and processing priority used to represent the privacy processing of privacy data, which is determined by the amount of privacy data in the trusted data space and the privacy processing requirements, and includes: privacy processing layer and privacy processing level.

[0132] In this embodiment, performing hierarchical processing on the privacy data to be processed according to the privacy processing layers means processing the privacy data to be processed in stages, so as to improve the privacy processing efficiency.

[0133] In this embodiment, load balancing processing refers to privacy processing performed on the privacy data to be processed according to the privacy processing level, distributed privacy processing, and elastic expansion processing.

[0134] In this embodiment, data volume distribution refers to the data distribution of the privacy data to be processed in each privacy processing node.

[0135] In this embodiment, the amount of privacy data refers to the amount of real privacy data to be processed at the privacy processing node, and is used to indicate the amount of privacy information contained in the privacy data to be processed.

[0136] In this embodiment, the load migration amount refers to the load amount that each privacy processing node in the trusted data space needs to migrate to other privacy processing nodes, which is used to achieve privacy processing of privacy data under high load conditions. For example, the load b1 at the privacy processing node a1 corresponding to the high load condition is migrated to the privacy processing node a2 corresponding to the low load condition.

[0137] In this embodiment, the processing order of the privacy data to be processed is determined according to the data volume distribution and the privacy processing level of the privacy data to be processed, and the privacy data to be processed with a large data volume distribution and a high privacy processing level is processed first.

[0138] The working principle and beneficial effects of the above technical solution are: by setting the privacy processing level, obtaining the data volume distribution and privacy data volume of the privacy data to be processed, determining the privacy processing level of the privacy data to be processed, combining distributed privacy processing and elastic expansion processing, and performing load balancing on the privacy data to be processed, which is conducive to efficient processing of privacy data in the trusted data space under high load conditions.

[0139] Embodiment 7:

[0140] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, further comprising:

[0141] The privacy processing sequence unit is used to prioritize distributed privacy processing and elastic expansion processing of the privacy data to be processed when it is detected that the trusted data space is under high load;

[0142] If the distributed privacy processing results show that the trusted data space is still handling a high load, load balancing will be performed on the privacy data to be processed.

[0143] The working principle and beneficial effects of the above technical solution are: by giving priority to distributed privacy processing and elastic expansion processing of the privacy data to be processed, and then load balancing processing of the privacy data to be processed, and setting the privacy processing order, efficient privacy processing can be achieved.

[0144] Embodiment 8:

[0145] The embodiment of the present invention provides a privacy data processing system based on a trusted data space, and a privacy processing optimization module, including:

[0146] A privacy processing optimization unit, used to obtain the load status of the trusted data space that has completed load balancing processing of the privacy data to be processed;

[0147] When the load condition of the trusted data space is high, and when it is determined that the trusted data space is continuously in a high load condition, the privacy processing algorithm of the privacy data to be processed is optimized according to the preset privacy processing algorithm, wherein the preset privacy processing algorithm includes: same-station encryption algorithm, secure multi-party computing algorithm and differential privacy computing algorithm.

[0148] In this embodiment, the preset privacy processing algorithm refers to the algorithm used by the trusted data space for privacy processing. By optimizing the privacy processing algorithm of the privacy data to be processed, the privacy processing efficiency can be improved, thereby achieving privacy processing of the privacy data when the trusted data space is under high load.

[0149] The working principle and beneficial effect of the above technical solution are: when the trusted data space is continuously under high load, the privacy processing algorithm of the privacy data to be processed is optimized, which is further conducive to the efficient processing of privacy data in the trusted data space under high load conditions.

[0150] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention 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. However, 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 embodiments of the present invention.

Claims

1. A privacy data processing system based on a trusted data space, characterized in that: include: The distributed architecture module is used to obtain the pending privacy data in the trusted data space when it is detected that the trusted data space is under high load, and to build a distributed architecture to perform distributed privacy processing on the pending privacy data; The elastic expansion module is used to obtain the configuration data of the trusted data space, set the elastic expansion strategy, and perform elastic expansion processing on the privacy data to be processed according to the processing configuration requirements and configuration data of the privacy data to be processed, including: A configuration data unit, used to obtain configuration data of the trusted data space, wherein the configuration data includes: resource configuration data, node configuration data, memory capacity configuration data, network bandwidth configuration data, and privacy processing performance configuration data; The elastic expansion unit is used to set elastic expansion strategies and obtain the processing configuration requirements of the privacy data to be processed when it is detected that the trusted data space is under high load; Obtain the currently enabled privacy processing nodes and currently disabled privacy processing nodes of the trusted data space, and enable the currently disabled privacy processing nodes or expand the configuration data of the currently enabled privacy processing nodes according to the processing configuration requirements of the privacy data to be processed, the configuration data of the currently enabled privacy processing nodes, and the configuration data of the currently disabled privacy processing nodes, so as to elastically expand the privacy data to be processed; The hierarchical load module is used to set the privacy processing level, obtain the data volume distribution and amount of privacy data to be processed, determine the privacy processing level of the privacy data to be processed, and perform load balancing on the privacy data to be processed in combination with distributed privacy processing and elastic expansion processing. Specifically, it includes: A privacy processing level unit, used to set the privacy processing level of the trusted data space according to the privacy data volume and privacy processing requirements of the private data in the trusted data space, wherein the privacy processing level refers to: a privacy processing layer and a privacy processing level; The privacy data to be processed is processed in layers according to the privacy processing layer, and data preprocessing is performed on the privacy basic layer to remove duplicate data in the privacy data to be processed. The privacy processing layer includes: a privacy basic layer, a privacy encryption layer, a privacy comprehensive processing layer, and a privacy aggregation layer; Perform data encryption processing on the privacy data to be processed after data preprocessing in the privacy encryption layer; In the privacy comprehensive processing layer, the privacy data to be processed after data encryption is processed is load balanced by combining distributed privacy processing and elastic expansion processing; Summarize the load balancing processing results at the data aggregation layer; Determine the processing order of the privacy data to be processed in the same privacy processing layer according to the privacy processing level; A privacy processing node in the trusted data space is randomly selected as the coordinate origin, a coordinate system is established, and the data volume distribution and the amount of privacy data to be processed are obtained according to the privacy data to be processed of the privacy processing node in the trusted data space; A load balancing processing unit, used to determine the privacy processing nodes with high load and the privacy processing nodes with low load in the trusted data space according to the data volume distribution of the privacy data to be processed, combined with distributed privacy processing and elastic expansion processing, and obtain the load migration amount of the trusted data space; ;in, Indicates the load migration amount of the trusted data space; Indicates At the privacy processing node under high load The data quantification value of the privacy data to be processed; Indicates The privacy processing node in the low load case The data quantification value of processed privacy data; Indicates At the privacy processing node under high load The probability that the private data to be processed is the real private data to be processed; Indicates The amount of privacy data to be processed at the privacy processing node under high load conditions; The number of privacy processing nodes representing high load conditions in the trusted data space; The number of privacy processing nodes representing low load conditions in the trusted data space; Indicates The number of privacy data to be processed at the privacy processing node under high load conditions; Determine the processing order of the privacy data to be processed based on the data volume distribution and privacy processing level of the privacy data to be processed, and perform load balancing on the privacy data to be processed based on the load migration volume of the trusted data space; The privacy processing optimization module is used to optimize the privacy processing algorithm of the privacy data to be processed when the trusted data space is continuously under high load.

2. A privacy data processing system based on a trusted data space according to claim 1, characterized in that: Distributed architecture modules, including: A load monitoring unit is used to monitor the load of the trusted data space in real time, obtain a set load threshold, and determine that the trusted data space is in a high load state when the current load threshold of the trusted data space is not lower than the set load threshold; When the current load value of the trusted data space is lower than the set load threshold, it is determined that the trusted data space is in a low load state; The to-be-processed privacy data unit is used to obtain the to-be-processed privacy data of the trusted data space when it is monitored that the trusted data space is in a high-load situation, wherein the to-be-processed privacy data includes: to-be-processed real privacy data and to-be-processed virtual privacy data; A distributed architecture unit is used to obtain the privacy processing requirements and data characteristics of the privacy data to be processed, divide the privacy data to be processed according to the privacy processing requirements and data characteristics, and obtain the privacy sub-data to be processed; Obtain the privacy processing nodes of the trusted data space, build a distributed architecture, randomly allocate the privacy sub-data to be processed according to the privacy processing resources of the privacy processing nodes, and perform distributed privacy processing; When the privacy processing node completes the distributed privacy processing, the distributed privacy processing results are aggregated and merged.

3. A privacy data processing system based on a trusted data space according to claim 2, characterized in that: Load monitoring unit, comprising: The load collection block is used to obtain the load data of the trusted data space from the privacy processing node of the trusted data space in real time according to the preset load indicators, wherein the load indicators include: CPU utilization index, memory utilization index, read and write response efficiency index, network bandwidth utilization index and privacy processing task volume index; A load threshold block is used to set the total load threshold of the trusted data space and the node load threshold of the privacy processing node of the trusted data space, and divide the load situation of the trusted data space into a high load situation and a low load situation; A load determination block, used to determine that the trusted data space is in a high load condition when the current node load value of the trusted data space is not lower than the node load threshold or the current total space load value is not lower than the total space load threshold; When the current node load values ​​of the trusted data space are all lower than the node load threshold and the current space total load value is lower than the space total load threshold, it is determined that the trusted data space is in a low load condition.

4. A privacy data processing system based on a trusted data space according to claim 3, characterized in that: The privacy data units to be processed include: The pending privacy data block is used to obtain the privacy data of the trusted data space when it is monitored that the trusted data space is under high load, and to determine the pending privacy data of the trusted data space according to the total space load threshold and the node load threshold, wherein the privacy data of the trusted data space includes: pending privacy data and processed privacy data.

5. The privacy data processing system based on a trusted data space according to claim 1, characterized in that: Also includes: The privacy processing sequence unit is used to prioritize distributed privacy processing and elastic expansion processing of the privacy data to be processed when it is detected that the trusted data space is under high load; If the distributed privacy processing results show that the trusted data space is still handling a high load, load balancing will be performed on the privacy data to be processed.

6. A privacy data processing system based on a trusted data space according to claim 1, characterized in that: Privacy processing optimization module, including: A privacy processing optimization unit, used to obtain the load status of the trusted data space that has completed load balancing processing of the privacy data to be processed; When the load condition of the trusted data space is high, and when it is determined that the trusted data space is continuously in a high load condition, the privacy processing algorithm of the privacy data to be processed is optimized according to the preset privacy processing algorithm, wherein the preset privacy processing algorithm includes: same-station encryption algorithm, secure multi-party computing algorithm and differential privacy computing algorithm.

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