Data Security Assessment Method and Assessment System

Abstract

This application relates to a data security evaluation method and an evaluation system. The method includes obtaining sample stored data and backup stored data of the sample data, and the number of the backup stored data is at least one; evaluating the consistency between the sample stored data and the backup stored data to obtain a consistency result; giving a security value of the sample stored data according to the consistency result, where the security value is the recovery probability of the sample stored data. Obtaining the backup stored data of the sample data includes reading the backup time, backup address, and backup range in the backup log. When evaluating the consistency between the sample stored data and the backup stored data, the evaluation is performed according to the backup time, backup address, and backup range. The data security evaluation method and evaluation system disclosed in this application can evaluate the backup data to evaluate the accuracy of using the backup data for data recovery.

Description

Technical Field

[0001] This application relates to the field of data security technology, and in particular, to a data security evaluation method and an evaluation system. Background Art

[0002] Data security refers to a series of measures and technologies to protect data from unauthorized access, use, disclosure, damage, or tampering. Its goal is to ensure the confidentiality, integrity, and availability of data. Data security involves multiple aspects such as collection, access, transmission, storage, and backup.

[0003] Data security in the collection stage involves data desensitization and data leakage, etc. Data security in the access stage involves permission management and dissemination scope, etc. Data security in the transmission stage involves data encryption and channel security, etc. Data security in the storage and backup stage involves data backup and data recovery, etc.

[0004] In the data backup stage, the currently used backup methods mainly focus on direct backup, and some also adopt off-site backup and cloud backup, aiming to be able to recover data. In the backup stage, multiple verification methods are used to ensure the accuracy of the backup data. However, if the backup data is interfered with during storage, the backup data may become abnormal, and at this time, accurate data recovery cannot be performed using the abnormal backup data. Summary of the Invention

[0005] This application provides a data security evaluation method and an evaluation system, which can evaluate backup data to evaluate the accuracy of data recovery using the backup data.

[0006] The above object of this application is achieved through the following technical solutions:

[0007] In a first aspect, this application provides a data security evaluation method, including:

[0008] Obtaining sample storage data and backup storage data of sample data, where the number of backup storage data is at least one;

[0009] Evaluating the consistency between the sample storage data and the backup storage data to obtain a consistency result;

[0010] Giving a security value for the sample storage data according to the consistency result, where the security value is the recovery probability of the sample storage data;

[0011] Among them, obtaining the backup storage data of the sample data includes reading the backup time, backup address, and backup range in the backup log;

[0012] When evaluating the consistency between the sample storage data and the backup storage data, the evaluation is carried out according to the backup time, backup address, and backup range.

[0013] In a possible implementation of the first aspect, evaluating the consistency between the evaluation sample storage data and the backup storage data includes:

[0014] Generating a first inspection curve using the sample storage data and generating a second inspection curve using the backup storage data;

[0015] Generating a first spectrogram and a second spectrogram using the first inspection curve and the second inspection curve respectively;

[0016] Determining the differences between the first spectrogram and the second spectrogram, with the differences located in the second spectrogram;

[0017] Generating a screening curve using the differences and superimposing the screening curve on the second inspection curve, and determining the starting position and the ending position of the screening curve on the second inspection curve;

[0018] Determining the data anomaly region according to the starting position and the ending position.

[0019] In a possible implementation of the first aspect, generating a first inspection curve using the sample storage data includes:

[0020] Selecting an inspection area on the sample storage data and sequentially creating inspection data blocks within the inspection area, with the same length between adjacent inspection data blocks;

[0021] Accumulating the numbers included in the inspection data blocks to obtain an accumulated value;

[0022] Creating a first inspection curve with the sequential position of the inspection data block as the abscissa and the accumulated value of the inspection data block as the ordinate;

[0023] Wherein, the method of generating a second inspection curve using the backup storage data is the same as the method of generating a first inspection curve using the sample storage data.

[0024] In a possible implementation of the first aspect, it further includes evaluating the smoothness of the first inspection curve and adjusting the accumulated value of the corresponding inspection data block according to the smoothness.

[0025] In a possible implementation of the first aspect, evaluating the smoothness of the first inspection curve includes:

[0026] Randomly selecting multiple points on the first inspection curve, denoted as inspection points;

[0027] Sequentially calculating the differences between adjacent inspection points to obtain a difference sequence, and at the same time calculating the second difference sequence of the difference sequence;

[0028] Taking the fluctuation range of the second difference sequence as the smoothness value of the first inspection curve.

[0029] In a possible implementation of the first aspect, adjusting the accumulated value corresponding to the inspection data block includes:

[0030] Select at least one point on the second-order difference sequence as an adjustment point, and the number of adjustment points is multiple;

[0031] Change the value of the adjustment point so that the smoothness value of the first inspection curve is greater than or equal to the allowable value;

[0032] Assign the changed value of the adjustment point to the corresponding inspection data block and adjust the accumulated value of the inspection data block.

[0033] In a possible implementation of the first aspect, after determining the data abnormal area, it further includes:

[0034] Repeatedly select inspection points on the first inspection curve, and there are two groups of inspection points located at the starting position and the ending position of the data abnormal area respectively;

[0035] Two inspection points in one group are respectively given positive adjustment and negative adjustment;

[0036] Determine the starting position and the ending position of the screening curve on the second inspection curve again.

[0037] In the second aspect, the present application provides a data security evaluation device, including:

[0038] A data acquisition unit, configured to obtain sample storage data and backup storage data of sample data, and the number of backup storage data is at least one;

[0039] A data evaluation unit, configured to evaluate the consistency of the sample storage data and the backup storage data to obtain a consistency result;

[0040] A result output unit, configured to give a security value of the sample storage data according to the consistency result, and the security value is the recovery probability of the sample storage data;

[0041] Wherein, obtaining the backup storage data of the sample data includes reading the backup time, backup address and backup range in the backup log;

[0042] When evaluating the consistency of the sample storage data and the backup storage data, evaluate according to the backup time, backup address and backup range.

[0043] In the third aspect, the present application provides a data security evaluation system, and the system includes:

[0044] One or more memories, configured to store instructions; and

[0045] One or more processors, configured to call and run the instructions from the memory and execute the method as described in the first aspect and any possible implementation manners of the first aspect.

[0046] In a fourth aspect, the present application provides a computer-readable storage medium, which includes:

[0047] A program, when the program is run by a processor, the method as described in the first aspect and any possible implementation manners of the first aspect is executed.

[0048] In a fifth aspect, the present application provides a computer program product, including program instructions, when the program instructions are run by a computing device, the method as described in the first aspect and any possible implementation manners of the first aspect is executed.

[0049] In a sixth aspect, the present application provides a chip system, which includes a processor for implementing the functions involved in the above aspects, for example, generating, receiving, sending, or processing the data and / or information involved in the above method.

[0050] The chip system may be composed of chips or may include chips and other discrete devices.

[0051] In a possible design, the chip system further includes a memory for storing necessary program instructions and data. The processor and the memory may be decoupled and disposed on different devices, connected by wire or wirelessly, or the processor and the memory may also be coupled on the same device. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 is a schematic block diagram of the step flow of the data security assessment method provided by the present application.

[0053] Figure 2 is a schematic diagram of abnormal data existing in the backup stored data provided by the present application.

[0054] Figure 3 is a schematic diagram of a first inspection curve provided by the present application.

[0055] Figure 4 is a schematic diagram of a first spectrogram provided by the present application.

[0056] Figure 5 is a schematic diagram of a second spectrogram provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0057] The following further elaborates on the technical solutions in the present application with reference to the accompanying drawings.

[0058] This application discloses a data security assessment method. Please refer to Figure 1 In some examples, the data security assessment method disclosed in this application includes the following steps:

[0059] S101, Obtain the sample stored data and the backup stored data of the sample data, and the number of backup stored data is at least one;

[0060] S102, Evaluate the consistency between the sample stored data and the backup stored data to obtain a consistency result;

[0061] S103, Give a security value for the sample stored data according to the consistency result, and the security value is the recovery probability of the sample stored data;

[0062] Among them, obtaining the backup stored data of the sample data includes reading the backup time, backup address, and backup range in the backup log;

[0063] When evaluating the consistency between the sample stored data and the backup stored data, evaluate according to the backup time, backup address, and backup range.

[0064] Overall, the problem to be solved by this application is to determine whether the sample stored data and the backup stored data of the sample data are consistent. After obtaining the backup stored data of the sample data, the consistency between the sample stored data and the backup stored data will be evaluated.

[0065] Here, the part of the backup stored data that is different from the sample stored data is called storage error (abnormal data). The role of evaluating consistency is to determine the number and location of storage errors, as Figure 2 shown.

[0066] For example, for verifying the consistency of two sets of data, currently, the MD5 algorithm is used for verification. The core idea of the MD5 algorithm is to transform input data of any length through a series of complex transformations, and finally generate a 128-bit hash value. This algorithm can be used to compare whether two sets of data are consistent.

[0067] For example, if both sets of data are 10,000 bits, two 128-bit hash values will be generated at this time. If these two 128-bit hash values are the same, it means the two sets of data are the same, otherwise it means the two sets of data are different. One disadvantage of this method is that it cannot determine where the differences are and also cannot determine the number of differences.

[0068] The specific method for evaluating the consistency between the sample stored data and the backup stored data is:

[0069] S201, Generate a first check curve using the sample stored data and a second check curve using the backup stored data;

[0070] S202, generate a first spectrogram and a second spectrogram using the first inspection curve and the second inspection curve respectively;

[0071] S203, determine the differences between the first spectrogram and the second spectrogram, and the differences are in the second spectrogram;

[0072] S204, generate a screening curve using the differences and superimpose the screening curve on the second inspection curve, and determine the starting position and the ending position of the screening curve on the second inspection curve;

[0073] S205, determine the data anomaly region according to the starting position and the ending position.

[0074] The content in steps S201 to S205 adopts a method of grouping the data. One group of data represents a point, and these points are arranged in order in the coordinate system. The abscissa of the point is the serial number of the data grouping, and the ordinate of the point is the cumulative value of the data in the data grouping.

[0075] Connecting these points together in order and performing smoothing processing can obtain a curve, which is the first inspection curve generated using the sample stored data mentioned in step S201 ( Figure 3 as shown) and the second inspection curve generated using the backup stored data (for reference Figure 3 ).

[0076] Then in step S202, a first spectrogram ( Figure 4 as shown) and a second spectrogram ( Figure 5 as shown, Figure 5 the dotted line in which indicates the difference) are generated using the first inspection curve and the second inspection curve respectively. The first spectrogram represents the composition of the first inspection curve, and the second spectrogram represents the composition of the second inspection curve. Then in step S203, the differences between the first spectrogram and the second spectrogram are determined, and the differences are in the second spectrogram.

[0077] In step S204, a screening curve is generated using the differences and the screening curve is superimposed on the second inspection curve, and the starting position and the ending position of the screening curve on the second inspection curve are determined. Here, the method of generating the screening curve using the differences is to generate a wavelet (i.e., the screening curve) based on the parameters (frequency, amplitude) of the differences, and then superimpose the screening curve on the second inspection curve.

[0078] Superimposing the screening curve on the second inspection curve will obtain a new waveform, which has a starting position and an ending position. At this time, the data anomaly region can be determined according to the starting position and the ending position.

[0079] The specific method is as follows: Both the starting position and the ending position can be determined by coordinates, that is, the horizontal coordinate range of the data anomaly area is determined. At this time, it is necessary to appropriately expand the horizontal coordinate range of the data anomaly area to determine the horizontal coordinate range of the data anomaly area. The data groups within the horizontal coordinate range of the data anomaly area are all suspected objects. At this time, verification is performed using, for example, the MD5 algorithm.

[0080] Using this method, all data anomaly areas can be found in one processing process, and then storage errors can be screened according to the data anomaly areas.

[0081] The method of using the sample storage data to generate the first inspection curve is as follows:

[0082] Select an inspection area on the sample storage data and sequentially create inspection data blocks within the inspection area. The lengths between adjacent inspection data blocks are the same;

[0083] Accumulate the numbers included in the inspection data block to obtain an accumulated value;

[0084] Create the first inspection curve with the sequential position of the inspection data block as the abscissa and the accumulated value of the inspection data block as the ordinate;

[0085] Among them, the method of using the backup storage data to generate the second inspection curve is the same as the method of using the sample storage data to generate the first inspection curve.

[0086] In some examples, a step of evaluating the smoothness of the first inspection curve and adjusting the accumulated value of the corresponding inspection data block according to the smoothness is added. The purpose of this step is to further clarify the data anomaly area. It should be understood that when there is a storage error in the data block, the following situations will occur:

[0087] Single-bit error:

[0088] 1010010101010101001010101……

[0089] 1010010101010101001010100……

[0090] Multi-bit error:

[0091] 1010010101010101001010101……

[0092] 1010011101010101001110100……

[0093] At this time, the accumulated value obtained may have a very small difference, which will lead to inaccurate positioning when determining the data abnormal area. It is necessary to evaluate the smoothness of the first inspection curve and adjust the accumulated value of the corresponding inspection data block according to the smoothness. The purpose of adjusting the accumulated value of the corresponding inspection data block is to amplify the difference.

[0094] The specific method for evaluating the smoothness of the first inspection curve is as follows:

[0095] S301, randomly select multiple points on the first inspection curve and record them as inspection points;

[0096] S302, sequentially calculate the differences between adjacent inspection points to obtain a difference sequence, and at the same time calculate the second-order difference sequence of the difference sequence;

[0097] S303, use the fluctuation range of the second-order difference sequence as the smoothness value of the first inspection curve.

[0098] The content in steps S301 to S303 determines the smoothness value of the first inspection curve according to the change degree of the differences of the inspection points.

[0099] The method for adjusting the accumulated value of the corresponding inspection data block is as follows:

[0100] Select at least one point on the second-order difference sequence as an adjustment point, and the number of adjustment points is multiple;

[0101] Change the value of the adjustment point to make the smoothness value of the first inspection curve greater than or equal to the allowable value;

[0102] Assign the changed value of the adjustment point to the corresponding inspection data block and adjust the accumulated value of the inspection data block.

[0103] After determining the data abnormal area, the following method is also required for processing:

[0104] S401, repeatedly select inspection points on the first inspection curve, and there are two groups of inspection points located at the starting position and the ending position of the data abnormal area respectively;

[0105] S402, assign positive adjustment and negative adjustment to the two inspection points in one group respectively;

[0106] S403, determine the starting position and the ending position of the screening curve on the second inspection curve again.

[0107] The content in steps S401 to S403 further clarifies the start position and end position of the data anomaly area. The specific method is to select checkpoints at the start position and end position of the data anomaly area respectively, and then assign positive adjustment and negative adjustment to the two checkpoints in a group respectively, aiming to amplify the difference. Finally, determine the start position and end position of the screening curve on the second check curve again.

[0108] When determining the start position and end position of the data anomaly area, it may be impossible to determine. This is because if there are exactly two storage errors, the storage errors cannot be recognized. At this time, it is necessary to divide the data block multiple times for inspection to reduce the probability that the storage errors cannot be recognized.

[0109] This application also provides a data security evaluation device, including:

[0110] A data acquisition unit, used to obtain the sample storage data and the backup storage data of the sample data, and the number of backup storage data is at least one;

[0111] A data evaluation unit, used to evaluate the consistency between the sample storage data and the backup storage data, and obtain a consistency result;

[0112] A result output unit, used to give the security value of the sample storage data according to the consistency result, and the security value is the recovery probability of the sample storage data;

[0113] Among them, obtaining the backup storage data of the sample data includes reading the backup time, backup address and backup range in the backup log;

[0114] When evaluating the consistency between the sample storage data and the backup storage data, evaluate according to the backup time, backup address and backup range.

[0115] Furthermore, it also includes:

[0116] A first generation unit, used to generate a first check curve using the sample storage data and generate a second check curve using the backup storage data;

[0117] A second generation unit, used to generate a first spectrogram and a second spectrogram using the first check curve and the second check curve respectively;

[0118] A difference determination unit, used to determine the difference between the first spectrogram and the second spectrogram, and the difference is located in the second spectrogram;

[0119] A first processing unit, used to generate a screening curve using the difference and superimpose the screening curve on the second check curve, and determine the start position and end position of the screening curve on the second check curve;

[0120] A second processing unit for determining a data anomaly region based on a starting position and an ending position.

[0121] Furthermore, it further includes:

[0122] A data block creation unit for selecting an inspection region on the sample storage data and sequentially creating inspection data blocks within the inspection region, with the same length between adjacent inspection data blocks;

[0123] An accumulation unit for accumulating the numbers included in the inspection data blocks to obtain an accumulated value;

[0124] A creation unit for creating a first inspection curve with the sequential position of the inspection data block as the abscissa and the accumulated value of the inspection data block as the ordinate;

[0125] Among them, the method of generating a second inspection curve using the backup storage data is the same as the method of generating the first inspection curve using the sample storage data.

[0126] Furthermore, it further includes evaluating the smoothness of the first inspection curve and adjusting the accumulated value of the corresponding inspection data block according to the smoothness.

[0127] Furthermore, it further includes:

[0128] A first selection unit for randomly selecting multiple points on the first inspection curve, denoted as inspection points;

[0129] A third processing unit for sequentially calculating the differences between adjacent inspection points to obtain a difference sequence, and simultaneously calculating the second difference sequence of the difference sequence;

[0130] A result unit for using the fluctuation range of the second difference sequence as the smoothness value of the first inspection curve.

[0131] Furthermore, it further includes:

[0132] A second selection unit for selecting at least one point as an adjustment point on the second difference sequence, and the number of adjustment points is multiple;

[0133] A first numerical adjustment unit for changing the value of the adjustment point to make the smoothness value of the first inspection curve greater than or equal to the allowable value;

[0134] A fourth processing unit for assigning the changed value of the adjustment point to the corresponding inspection data block and adjusting the accumulated value of the inspection data block.

[0135] Furthermore, it further includes:

[0136] A third selection unit for repeatedly selecting inspection points on the first inspection curve, and there are two groups of inspection points located at the starting position and the ending position of the data anomaly region respectively;

[0137] A second numerical value adjustment unit for respectively assigning forward adjustment and reverse adjustment to two checkpoints in a group;

[0138] A position re-determination unit for re-determining the starting position and the ending position of the screening curve on the second check curve.

[0139] In one example, the units in any of the above devices may be one or more integrated circuits configured to implement the above methods. For example: one or more application specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0140] Again, when the units in the device can be implemented in the form of a processing element scheduler, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call programs. Again, these units may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0141] In this application, names may be assigned to various objects such as various messages / information / devices / network elements / systems / devices / actions / operations / processes / concepts, etc. It can be understood that these specific names do not constitute a limitation on the relevant objects, and the assigned names may change with factors such as the scenario, context, or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from the functions and technical effects reflected / executed in the technical solution.

[0142] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0143] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0144] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0145] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0146] It should also be understood that in each embodiment of this application, the first, second, etc. are only used to indicate that multiple objects are different. For example, the first time window and the second time window are only used to indicate different time windows. And it should not have any impact on the time window itself. The above first, second, etc. should not impose any restrictions on the embodiments of this application.

[0147] It should also be understood that in each embodiment of this application, if there is no special explanation and logical conflict, the terms and / or descriptions between different embodiments are consistent and can be mutually referred to. The technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0148] When the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The aforementioned computer-readable storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0149] This application also provides a data security assessment system, which includes:

[0150] One or more memories for storing instructions; and

[0151] One or more processors for calling and running the instructions from the memory and executing the methods described in the above content.

[0152] This application also provides a computer program product, which includes instructions that, when executed, cause the terminal device and the network device to perform the operations of the terminal device and the network device corresponding to the above methods.

[0153] This application also provides a chip system, which includes a processor for implementing the functions involved in the above content, for example, generating, receiving, sending, or processing the data and / or information involved in the above methods.

[0154] This chip system can be composed of chips or can include chips and other discrete devices.

[0155] The processor mentioned anywhere above can be a CPU, a microprocessor, an ASIC, or an integrated circuit for controlling the execution of the programs of the methods for transmitting the above feedback information.

[0156] In a possible design, this chip system further includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and set on different devices and connected by wired or wireless means to support the chip system in implementing various functions in the above embodiments. Or, the processor and the memory can also be coupled on the same device.

[0157] Optionally, the computer instructions are stored in a memory.

[0158] Optionally, the memory is a storage unit within the chip, such as a register, cache, etc. The memory can also be a storage unit outside the chip within the terminal, such as a ROM or other types of static storage devices that can store static information and instructions, a RAM, etc.

[0159] It can be understood that the memory in this application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0160] The non-volatile memory can be a ROM, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory.

[0161] The volatile memory can be a RAM, which is used as an external cache. There are various different types of RAM, such as a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDR SDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synch link dynamic random access memory (SLDRAM), and a direct memory bus random access memory.

[0162] The embodiments of this specific implementation manner are all preferred embodiments of this application, and do not limit the protection scope of this application accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the protection scope of this application.

Claims

1. A data security assessment method, characterized in that, Including: Obtaining the sample storage data and the backup storage data of the sample data, where the number of backup storage data is at least one; Evaluating the consistency between the sample storage data and the backup storage data to obtain a consistency result; Giving a security value for the sample storage data according to the consistency result, where the security value is the recovery probability of the sample storage data; Among them, obtaining the backup storage data of the sample data includes reading the backup time, backup address, and backup range in the backup log; When evaluating the consistency between the sample storage data and the backup storage data, the evaluation is performed according to the backup time, backup address, and backup range; Evaluating the consistency between the sample storage data and the backup storage data includes: Generating a first inspection curve using the sample storage data and generating a second inspection curve using the backup storage data; Generating a first spectrogram and a second spectrogram using the first inspection curve and the second inspection curve respectively; Determining the differences in the first spectrogram and the second spectrogram, where the differences are in the second spectrogram; Generating a screening curve using the differences and superimposing the screening curve on the second inspection curve to determine the starting position and ending position of the screening curve on the second inspection curve; Determining the data abnormal area according to the starting position and ending position; 2. The data security assessment method according to claim 1, wherein Generating a first inspection curve using the sample storage data includes: Selecting an inspection area on the sample storage data and sequentially creating inspection data blocks within the inspection area, where the lengths between adjacent inspection data blocks are the same; Accumulating the numbers included in the inspection data blocks to obtain an accumulated value; Creating a first inspection curve with the sequential position of the inspection data blocks as the abscissa and the accumulated value of the inspection data blocks as the ordinate; Among them, the method of generating a second inspection curve using the backup storage data is the same as the method of generating a first inspection curve using the sample storage data; 3. The data security assessment method according to claim 1 or 2, characterized in that, It also includes evaluating the smoothness of the first inspection curve and adjusting the accumulated value of the corresponding inspection data block according to the smoothness; 4. The data security assessment method according to claim 3, wherein Evaluating the smoothness of the first inspection curve includes: Randomly selecting multiple points on the first inspection curve and recording them as inspection points; Sequentially calculating the differences between adjacent inspection points to obtain a difference sequence, and at the same time calculating the second difference sequence of the difference sequence; Taking the fluctuation range of the second difference sequence as the smoothness value of the first inspection curve; 5. The data security assessment method according to claim 4, wherein Adjusting the accumulated value of the corresponding inspection data block includes: Selecting at least one point on the second difference sequence as an adjustment point, and the number of adjustment points is multiple; Changing the value of the adjustment point to make the smoothness value of the first inspection curve greater than or equal to the allowable value; Assigning the changed value of the adjustment point to the corresponding inspection data block and adjusting the accumulated value of the inspection data block; 6. The data security assessment method according to claim 4, wherein After determining the data abnormal area, it also includes: Repeatedly selecting inspection points on the first inspection curve, and there are two groups of inspection points located at the starting position and ending position of the data abnormal area respectively; Two inspection points in one group are respectively given positive adjustment and negative adjustment; Determining the starting position and ending position of the screening curve on the second inspection curve again; 7. Data security assessment device, characterized in that, Including: A data acquisition unit for obtaining the sample storage data and the backup storage data of the sample data, where the number of backup storage data is at least one; A data evaluation unit for evaluating the consistency between the sample storage data and the backup storage data to obtain a consistency result; A result output unit, configured to give a security value of the sample storage data according to the consistency result, where the security value is the recovery probability of the sample storage data; Among them, obtaining the backup storage data of the sample data includes reading the backup time, backup address, and backup range in the backup log; When evaluating the consistency between the sample storage data and the backup storage data, the evaluation is performed according to the backup time, backup address, and backup range; Evaluating the consistency between the sample storage data and the backup storage data includes: Generating a first check curve using the sample storage data and generating a second check curve using the backup storage data; Generating a first spectrogram and a second spectrogram using the first check curve and the second check curve respectively; Determining the difference between the first spectrogram and the second spectrogram, where the difference is located in the second spectrogram; Generating a screening curve using the difference and superimposing the screening curve on the second check curve, and determining the starting position and ending position of the screening curve on the second check curve; Determining the data anomaly area according to the starting position and the ending position.

8. Data security assessment system, characterized in that, The system includes: One or more memories, configured to store instructions; and One or more processors, configured to call and run the instructions from the memory and execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: A program, when the program is run by a processor, the method according to any one of claims 1 to 6 is executed.

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