Data encryption method and device, equipment and storage medium

Abstract

The invention relates to a data encryption method, apparatus and device, and a storage medium. The method comprises the steps of obtaining first geographic information of each sub-region in a target region, second geographic information of a plurality of data acquisition points in the target region, and monitoring data corresponding to the plurality of data acquisition points; for each data acquisition point, determining the sub-region to which the data acquisition point belongs based on the first geographic information of each sub-region and the second geographic information of the data acquisition point; and for each sub-region, encrypting the monitoring data corresponding to each data acquisition point included in the sub-region. According to the method and the device, the sub-regions to which the data acquisition points belong are determined to be divided, and the monitoring data corresponding to the data acquisition points in the same sub-region are encrypted, so that access permissions of data of different sub-regions can be allocated to different users, and the security of the data is further improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of data encryption, and in particular to a data encryption method, device, equipment and storage medium. Background Art

[0002] With the development of information technology and the advent of the data age, people often rely on a large amount of data collected in the early stage when making decisions, and in the process of data transmission and storage, data security needs to be ensured. Traditional methods often use overall data encryption to improve data security, but in the data usage link, even if the user only needs to access part of the data, it is necessary to obtain the complete encrypted data set, and it is impossible to set different access rights for different users, which greatly increases the risk of data leakage and seriously threatens data security. Therefore, how to encrypt data to improve data security is a technical problem that needs to be solved. Summary of the invention

[0003] In order to solve the above technical problems, the present disclosure provides a data encryption method, device, equipment and storage medium.

[0004] A first aspect of an embodiment of the present disclosure provides a data encryption method, the method comprising:

[0005] Acquire first geographic information of each sub-area in the target area, second geographic information of multiple data collection points in the target area, and monitoring data corresponding to the multiple data collection points;

[0006] For each data collection point, based on the first geographic information of each sub-area and the second geographic information of the data collection point, determining the sub-area to which the data collection point belongs;

[0007] For each sub-area, the monitoring data corresponding to each data collection point contained in the sub-area is encrypted.

[0008] Optionally, determining the sub-region to which each data collection point belongs based on the first geographic information of each sub-region and the second geographic information of the plurality of data collection points includes:

[0009] For each data collection point, based on the first geographic information of each sub-area and the second geographic information of the data collection point, the target parameters corresponding to each sub-area are calculated, and the sub-area with the smallest target parameter is determined as the sub-area to which the data collection point belongs.

[0010] Optionally, the first geographic information includes at least one of a first geographic coordinate of a center point, a first geographic feature vector, a data collection density, a regional correlation parameter, and a time change impact parameter, and the second geographic information includes at least one of a second geographic coordinate and a second geographic feature vector;

[0011] The calculating the target parameters corresponding to each sub-area based on the first geographic information of each sub-area and the second geographic information of the data collection point includes:

[0012] Calculating a first distance between each sub-area and the data collection point based on the first geographical coordinates of the center point of each sub-area and the second geographical coordinates of the data collection point;

[0013] Based on the first geographic feature vector of each sub-region and the second geographic feature vector of the data collection point, calculating the geographic feature similarity between each sub-region and the data collection point;

[0014] Based on the first distance between each sub-region and the data collection point, the geographical feature similarity between each sub-region and the data collection point, and the data collection density, regional correlation parameter and time change impact parameter of each sub-region, the target parameter corresponding to each sub-region is determined.

[0015] Optionally, the time variation influencing parameter is determined based on at least one of the order of Fourier series expansion, the period length, and the period variation frequency.

[0016] Optionally, the area association parameter is determined based on at least one of the second distance between the current sub-area and other sub-areas, the standard deviation of the second distance, the first geographic feature vector of the current sub-area, the first geographic feature vector of other sub-areas, the standard deviation of the geographic feature vector, the timestamp of the current sub-area, the timestamp of other sub-areas, and the standard deviation of time.

[0017] Optionally, the encryption method of the monitoring data includes homomorphic encryption. After encrypting the monitoring data corresponding to each data collection point contained in each sub-area, the method further includes:

[0018] Perform privacy computing on homomorphically encrypted monitoring data.

[0019] Optionally, the target area is a target water system basin, and the monitoring data includes at least one of shipping data, ship data, meteorological data, hydrological data and geological data.

[0020] A second aspect of an embodiment of the present disclosure provides a data encryption device, the device comprising:

[0021] An acquisition module, used to acquire first geographic information of each sub-area in the target area, second geographic information of multiple data collection points in the target area, and monitoring data corresponding to the multiple data collection points;

[0022] A region division module, for determining, for each data collection point, the sub-region to which the data collection point belongs based on the first geographic information of each sub-region and the second geographic information of the data collection point;

[0023] The encryption module is used to encrypt, for each sub-area, the monitoring data corresponding to each data collection point contained in the sub-area.

[0024] A third aspect of an embodiment of the present disclosure provides a computer device, including a memory and a processor, and a computer program, wherein the computer program is stored in the memory, and when the computer program is executed by the processor, the data encryption method as described in the first aspect above is implemented.

[0025] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the data encryption method of the first aspect described above is implemented.

[0026] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:

[0027] In the data encryption method, apparatus, device and storage medium provided in the embodiments of the present disclosure, by obtaining the first geographic information of each sub-area in the target area, the second geographic information of multiple data collection points in the target area and the monitoring data corresponding to the multiple data collection points, for each data collection point, based on the first geographic information of each sub-area and the second geographic information of the data collection point, the sub-area to which the data collection point belongs is determined, and for each sub-area, the monitoring data corresponding to each data collection point contained in the sub-area is encrypted. The sub-area to which the data collection point belongs can be divided, and the monitoring data corresponding to each data collection point in the same sub-area can be encrypted, so that when users need to access data, access rights to data in different sub-areas are allocated to different users, thereby further improving data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0030] Figure 1 is a flow chart of a data encryption method provided by an embodiment of the present disclosure;

[0031] Figure 2 is a structural schematic diagram of a data encryption device provided by an embodiment of the present disclosure;

[0032] Figure 3 It is a structural diagram of a computer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0033] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0034] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0035] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0036] Figure 1 1 is a flow chart of a data encryption method provided by an embodiment of the present disclosure. The method can be executed by a data encryption device. The data encryption device can be implemented in software and / or hardware. The data encryption device can be configured in an electronic device, such as a server or a terminal, wherein the terminal specifically includes a mobile phone, a computer or a tablet computer, etc. Figure 1 As shown, the data encryption method provided in this embodiment includes the following steps:

[0037] S101, obtaining first geographic information of each sub-area in a target area, second geographic information of multiple data collection points in the target area, and monitoring data corresponding to the multiple data collection points.

[0038] The target area in the embodiment of the present disclosure can be understood as a geographical area where detection data needs to be obtained, and the target area contains multiple data collection points. The sub-areas can be understood as multiple sub-areas obtained by dividing the target area in advance according to preset rules (such as longitude and latitude, geographical features, natural boundaries, etc.). Optionally, the target area can be a target water system basin, and the monitoring data can include at least one of shipping data, ship data, meteorological data, hydrological data, and geological data collected by each data collection point set in the water system basin.

[0039] The first geographic information in the disclosed embodiment can be understood as the geographic information of the sub-area, which may specifically include the geographic coordinates, geographic features, etc. of the sub-area. The second geographic information can be understood as the geographic information of the data collection point, which may specifically include the geographic coordinates, geographic features, etc. of the data collection point, which are not limited here.

[0040] In the disclosed embodiment, the data encryption device can obtain the first geographic information of each sub-area in the target area where the multiple data collection points are located, as well as the second geographic information and corresponding monitoring data of the multiple data collection points when it is necessary to encrypt the monitoring data corresponding to the multiple data collection points.

[0041] In an exemplary implementation of the disclosed embodiment, the data encryption device can obtain sub-area division information, first geographic information of each sub-area in the target area, and second geographic information of multiple data collection points from preset geographic information related files, and then obtain monitoring data corresponding to multiple data collection points through a preset monitoring data summary interface, and associate the monitoring data with the data collection points.

[0042] S102: For each data collection point, determine the sub-region to which the data collection point belongs based on the first geographic information of each sub-region and the second geographic information of the data collection point.

[0043] In the disclosed embodiment, the data encryption device can obtain the first geographic information of each sub-region and the second geographic information of multiple data collection points, and for each data collection point, according to a preset area division rule, use the first geographic information of each sub-region and the second geographic information of the current data collection point to determine the sub-region to which the current data collection point belongs, until all data collection points are partitioned.

[0044] In another exemplary implementation of the disclosed embodiment, the data encryption device may determine the sub-region where the current data collection point is located based on the current data collection point's geographical location and the boundary positions of each sub-region.

[0045] In another exemplary implementation of the disclosed embodiment, the data encryption device may perform feature matching on the first geographic information of each sub-region and the second geographic information of the current data collection point, and determine the sub-region with the highest matching degree with the current data collection point as the sub-region to which the current data collection point belongs.

[0046] S103: For each sub-area, encrypt the monitoring data corresponding to each data collection point contained in the sub-area.

[0047] In the embodiment of the present disclosure, the data encryption device can, after determining the sub-areas to which each data collection point belongs, determine, for each sub-area, each data collection point contained in the current sub-area, and encrypt the monitoring data corresponding to each data collection point contained in the current sub-area as a whole until the encryption of the monitoring data corresponding to each data collection point contained in each sub-area is completed.

[0048] In an exemplary implementation of the disclosed embodiment, the data encryption device can homomorphically encrypt the monitoring data corresponding to each data collection point contained in the current sub-area, and after the encryption is completed, directly perform privacy calculations on the homomorphically encrypted monitoring data, thereby eliminating the need to decrypt the data first, so that the calculation result remains encrypted, and only users with the decryption key can see the true value of the calculation result.

[0049] The disclosed embodiment obtains the first geographic information of each sub-area in the target area, the second geographic information of multiple data collection points in the target area, and the monitoring data corresponding to the multiple data collection points. For each data collection point, based on the first geographic information of each sub-area and the second geographic information of the data collection point, the sub-area to which the data collection point belongs is determined. For each sub-area, the monitoring data corresponding to each data collection point contained in the sub-area is encrypted. The sub-area to which the data collection point belongs can be divided, and the monitoring data corresponding to each data collection point in the same sub-area can be encrypted. Therefore, when the user needs to access the data, access rights to data of different sub-areas are allocated to different users, thereby further improving the security of the data.

[0050] In some embodiments, when executing S102, the data encryption device can calculate the target parameters corresponding to each sub-area for each data collection point based on the first geographic information of each sub-area and the second geographic information of the data collection point, and determine the sub-area with the smallest target parameter as the sub-area to which the data collection point belongs.

[0051] Among them, the target parameter is used to measure the regional division result of the data collection point. The smaller the value of the target parameter, the greater the probability that the data collection point belongs to the current sub-region.

[0052] Among them, the first geographic information includes at least one of the first geographic coordinates of the center point, the first geographic feature vector, the data collection density, the regional correlation parameter and the time change impact parameter, and the second geographic information includes at least one of the second geographic coordinates and the second geographic feature vector.

[0053] When calculating the target parameters corresponding to each sub-region, the data encryption device can calculate the first distance between each sub-region and the data collection point based on the first geographical coordinates of the center point of each sub-region and the second geographical coordinates of the data collection point, and calculate the geographical feature similarity between each sub-region and the data collection point based on the first geographical feature vector of each sub-region and the second geographical feature vector of the data collection point. The target parameters corresponding to each sub-region are determined based on the first distance between each sub-region and the data collection point, the geographical feature similarity between each sub-region and the data collection point, and the data collection density, regional correlation parameter, and time change influence parameter of each sub-region.

[0054] Specifically, the i-th timestamp t i The second geographic coordinate (x i ,y i ) belongs to the sub-region R j It can be expressed by the following formula:

[0055]

[0056] Where n is the number of sub-regions, x i is the horizontal coordinate of the second geographic coordinate of the i-th data collection point, c k is the horizontal coordinate of the first geographic coordinate of the center point of the kth sub-region, y i is the ordinate of the second geographic coordinate of the i-th data collection point, d k is the ordinate of the first geographic coordinate of the center point of the kth sub-region, represents the first distance between the kth sub-region and the i-th data collection point, α is the geographical feature weight, and v k is the first geographic feature vector of the kth sub-region, w i is the second geographic feature vector of the ith data collection point, v k ·w i It represents the similarity of geographical features between the kth sub-region and the ith data collection point, β is the data collection density weight, ρ k is the data collection density of the kth sub-region, γ is the correlation weight, A kl is the correlation parameter between the kth sub-region and the lth sub-region, δ is the time influence weight, ψ(t i) is the time-varying influencing parameter, which is used to characterize the influence of time factors on the regional division of data points. The kth sub-region target parameter can be obtained by express.

[0057] Optionally, the time variation influence parameter is used to characterize the influence of the time factor on determining the sub-region to which the data point belongs. The time variation influence parameter is determined based on at least one of the order of the Fourier series expansion, the period length, and the period variation frequency, and can be specifically expressed by the following formula:

[0058]

[0059] Among them, ψ(t i ) is the time-varying influence parameter, α′ k′ is the weight of the sine term at the k′th order, K is the order of the Fourier series expansion, T is the period length, β′ k′ is the weight of the cosine term at the k′th order, and k″ is the frequency of periodic variation.

[0060] Optionally, the regional association parameter is determined based on at least one of the second distance between the current sub-region and the other sub-regions, the standard deviation of the second distance, the first geographic feature vector of the current sub-region, the first geographic feature vector of the other sub-regions, the standard deviation of the geographic feature vector, the timestamp of the current sub-region, the timestamp of the other sub-regions, and the standard deviation of time. Specifically, the regional association parameter A between the kth sub-region and the lth sub-region is kl It can be expressed by the following formula:

[0061]

[0062] Among them, d kl is the second distance between the kth sub-region and the lth sub-region, σ d is the standard deviation of the second distance, σ f is the standard deviation of the geographic feature vector, σ t is the standard deviation of time, v k is the first geographic feature vector of the kth sub-region, v l is the first geographic feature vector of the lth sub-region, t k is the timestamp of the kth sub-region, t l is the timestamp of the lth sub-region.

[0063] Figure 2 Schematic diagram of a data encryption device provided by an embodiment of the present disclosure. Figure 2As shown, the data encryption device 200 includes: an acquisition module 210, a region division module 220, and an encryption module 230, wherein the acquisition module 210 is used to obtain the first geographic information of each sub-region in the target region, the second geographic information of multiple data collection points in the target region, and the monitoring data corresponding to the multiple data collection points; the region division module 220 is used to determine, for each data collection point, the sub-region to which the data collection point belongs based on the first geographic information of each sub-region and the second geographic information of the data collection point; the encryption module 230 is used to encrypt, for each sub-region, the monitoring data corresponding to each data collection point contained in the sub-region.

[0064] Optionally, the area division module 220 is specifically used to calculate, for each data collection point, the target parameters corresponding to each sub-area based on the first geographic information of each sub-area and the second geographic information of the data collection point, and determine the sub-area with the smallest target parameter as the sub-area to which the data collection point belongs.

[0065] Optionally, the first geographic information includes at least one of the first geographic coordinates of the center point, the first geographic feature vector, the data collection density, the regional association parameter and the time change influence parameter, and the second geographic information includes at least one of the second geographic coordinates and the second geographic feature vector; the area division module 220 includes: a first calculation unit, used to calculate the first distance between each sub-region and the data collection point based on the first geographic coordinates of the center point of each sub-region and the second geographic coordinates of the data collection point; a second calculation unit, used to calculate the geographic feature similarity between each sub-region and the data collection point based on the first geographic feature vector of each sub-region and the second geographic feature vector of the data collection point; a parameter determination unit, used to determine the target parameters corresponding to each sub-region based on the first distance between each sub-region and the data collection point, the geographic feature similarity between each sub-region and the data collection point, and the data collection density, the regional association parameter and the time change influence parameter of each sub-region.

[0066] Optionally, the time variation influencing parameter is determined based on at least one of the order of Fourier series expansion, the period length, and the period variation frequency.

[0067] Optionally, the area association parameter is determined based on at least one of the second distance between the current sub-area and other sub-areas, the standard deviation of the second distance, the first geographic feature vector of the current sub-area, the first geographic feature vector of other sub-areas, the standard deviation of the geographic feature vector, the timestamp of the current sub-area, the timestamp of other sub-areas, and the standard deviation of time.

[0068] Optionally, the encryption method of the monitoring data includes homomorphic encryption, and the data encryption device 200 also includes: a computing module, used to perform privacy computing on the monitoring data after homomorphic encryption.

[0069] Optionally, the target area is a target water system basin, and the monitoring data includes at least one of shipping data, ship data, meteorological data, hydrological data and geological data.

[0070] The data encryption device provided in this embodiment can execute the method described in any of the above embodiments. Its execution method and beneficial effects are similar and will not be repeated here.

[0071] Figure 3 It is a structural diagram of a computer device provided in an embodiment of the present disclosure.

[0072] like Figure 3 As shown, the computer device may include a processor 310 and a memory 320 storing computer program instructions.

[0073] Specifically, the processor 310 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0074] The memory 320 may include a large capacity memory for information or instructions. By way of example and not limitation, the memory 320 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 320 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 320 may be inside or outside the integrated gateway device. In a particular embodiment, the memory 320 is a non-volatile solid-state memory. In a particular embodiment, the memory 320 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (Electrically Erasable Programmable ROM, EEPROM), an electrically rewritable ROM (EAROM) or a flash memory, or a combination of two or more of these.

[0075] The processor 310 reads and executes the computer program instructions stored in the memory 320 to perform the steps of the data encryption method provided in the embodiment of the present disclosure.

[0076] In one example, the computer device may further include a transceiver 330 and a bus 340. Figure 3 As shown, the processor 310, the memory 320 and the transceiver 330 are connected via a bus 340 and communicate with each other.

[0077] The bus 340 includes hardware, software, or both. For example, but not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a Memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, the bus 340 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0078] The embodiments of the present disclosure also provide a computer-readable storage medium, which may store a computer program. When the computer program is executed by a processor, the processor implements the data encryption method provided by the embodiments of the present disclosure.

[0079] The above-mentioned storage medium may, for example, include a memory 320 of computer program instructions, and the above-mentioned instructions may be executed by the processor 310 of the data encryption device to complete the data encryption method provided by the embodiment of the present disclosure. Optionally, the storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a ROM, a random access memory (Random Access Memory, RAM), a compact disc read-only memory (Compact Disc ROM, CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc. The above-mentioned computer program may be written in any combination of one or more programming languages ​​to perform the program code for the operation of the embodiment of the present disclosure, and the programming language includes an object-oriented programming language, such as Java, C++, etc., and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device, partially on the remote computing device, or completely on the remote computing device or server.

[0080] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0081] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data encryption method, characterized in that: The method comprises: Acquire first geographic information of each sub-area in the target area, second geographic information of multiple data collection points in the target area, and monitoring data corresponding to the multiple data collection points; For each data collection point, based on the first geographic information of each sub-area and the second geographic information of the data collection point, determining the sub-area to which the data collection point belongs; For each sub-area, the monitoring data corresponding to each data collection point contained in the sub-area is encrypted.

2. The method according to claim 1, characterized in that The step of determining, for each data collection point, the sub-region to which the data collection point belongs based on the first geographic information of each sub-region and the second geographic information of the data collection point, includes: For each data collection point, based on the first geographic information of each sub-area and the second geographic information of the data collection point, the target parameters corresponding to each sub-area are calculated, and the sub-area with the smallest target parameter is determined as the sub-area to which the data collection point belongs.

3. The method according to claim 2, characterized in that The first geographic information includes at least one of a first geographic coordinate of a center point, a first geographic feature vector, a data collection density, a regional correlation parameter, and a time change impact parameter, and the second geographic information includes at least one of a second geographic coordinate and a second geographic feature vector; The calculating the target parameters corresponding to each sub-area based on the first geographic information of each sub-area and the second geographic information of the data collection point includes: Calculating a first distance between each sub-area and the data collection point based on the first geographical coordinates of the center point of each sub-area and the second geographical coordinates of the data collection point; Based on the first geographic feature vector of each sub-region and the second geographic feature vector of the data collection point, calculating the geographic feature similarity between each sub-region and the data collection point; Based on the first distance between each sub-region and the data collection point, the geographical feature similarity between each sub-region and the data collection point, and the data collection density, regional correlation parameter and time change impact parameter of each sub-region, the target parameter corresponding to each sub-region is determined.

4. The method according to claim 3, characterized in that The time-varying influencing parameter is determined based on at least one of the order of the Fourier series expansion, the period length, and the periodic variation frequency.

5. The method according to claim 3, characterized in that: The regional association parameter is determined based on at least one of the second distance between the current sub-region and the other sub-regions, the standard deviation of the second distance, the first geographic feature vector of the current sub-region, the first geographic feature vector of the other sub-regions, the standard deviation of the geographic feature vectors, the timestamp of the current sub-region, the timestamp of the other sub-regions, and the standard deviation of time.

6. The method according to claim 1, characterized in that The encryption method of the monitoring data includes homomorphic encryption. After encrypting the monitoring data corresponding to each data collection point contained in each sub-area, the method further includes: Perform privacy computing on homomorphically encrypted monitoring data.

7. The method according to claim 1, characterized in that The target area is a target water system basin, and the monitoring data includes at least one of shipping data, ship data, meteorological data, hydrological data and geological data.

8. A data encryption device, characterized in that: The device comprises: An acquisition module, used to acquire first geographic information of each sub-area in the target area, second geographic information of multiple data collection points in the target area, and monitoring data corresponding to the multiple data collection points; A region division module, for determining, for each data collection point, the sub-region to which the data collection point belongs based on the first geographic information of each sub-region and the second geographic information of the data collection point; The encryption module is used to encrypt, for each sub-area, the monitoring data corresponding to each data collection point contained in the sub-area.

9. A computer device, characterized in that: include: Memory; processor; and a computer program; wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the data encryption method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the data encryption method according to any one of claims 1 to 7 is implemented.

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