Safety guarantee method, device and equipment for data acquisition

Abstract

The invention discloses a security guarantee method, device and equipment for data acquisition, belongs to the field of data acquisition, and aims to solve the problems that (1) some data attributes of encrypted data are not changed, and (2) some data types have specific data attributes. Therefore, the data collector can firstly obtain the encrypted original data sent by the data sender, and for any original data, when the attribute data of the original data meets the preset attribute requirement, the original data is reserved as effective data, so that the original data is saved. The data type of the original data is represented to be the data type corresponding to the preset attribute requirement according to the fact that the data attribute meets the preset attribute requirement, that is, screening of the data type is achieved through the data attribute, data collection and filtering are achieved on the basis of encryption, the collected data are prevented from being leaked or tampered, and the encryption efficiency is improved. And the security of the collected data is improved.

Description

Technical Field

[0001] The present invention relates to the field of data collection, and in particular to a method, device and equipment for ensuring the safety of data collection. Background Art

[0002] The data collector can filter the collected raw data to retain or focus on the data parts that meet specific requirements. However, the relevant technology lacks a mature data collection security method. The data collector usually collects the raw data in plain text and directly filters the raw data in plain text. However, collecting the raw data in plain text may cause the collected data to be leaked or tampered with.

[0003] Therefore, how to provide a solution to the above technical problems is a problem that those skilled in the art need to solve at present. Summary of the invention

[0004] The purpose of the present invention is to provide a security assurance method, device and equipment for data collection. The data collector can first obtain the encrypted original data sent by the data sender. For any original data, when the attribute data of the original data meets the preset attribute requirements, the original data is retained as valid data. Since "data attributes meet the preset attribute requirements" represents that the data type of the original data is "the data type corresponding to the preset attribute requirements", that is, the present invention realizes the screening of data types through data attributes, realizes data collection and filtering on the basis of encryption, avoids the collected data from being leaked or tampered with, and improves the security of the collected data.

[0005] In order to solve the above technical problems, the present invention provides a data collection security method, which is applied to a data collector and comprises:

[0006] Obtain the encrypted original data sent by the data sender;

[0007] For any of the original data, determining whether data attributes of the original data meet preset attribute requirements, wherein the data attributes include length and / or format;

[0008] If satisfied, the original data is retained as valid data.

[0009] On the other hand, after determining whether the data attribute of any of the original data meets the preset attribute requirement, the data collection security assurance method further includes:

[0010] For any of the original data, determining whether the original data has a first type of preset label;

[0011] If so, the data type corresponding to the first type of preset label is determined according to the first corresponding relationship, and the original data and its corresponding data type are retained as valid data.

[0012] On the other hand, after obtaining the encrypted original data sent by the data sender, the data collection security assurance method further includes:

[0013] Determine whether there is a composite tag in the original data, wherein the composite tag refers to a tag composed of sub-tags on multiple original data;

[0014] If so, determining the data feature model portrait corresponding to the composite tag according to the second corresponding relationship;

[0015] The data feature model portrait and its corresponding original data are retained together as valid data, wherein the original data corresponding to the data feature model portrait refers to the original data of each sub-label of the composite label corresponding to the data feature model portrait.

[0016] On the other hand, the data collection security guarantee method also includes:

[0017] In response to the modification instruction, the first corresponding relationship and / or the second corresponding relationship is modified.

[0018] In order to solve the above technical problems, the present invention also provides a data collection security guarantee method, which is applied to the data sender, comprising:

[0019] Encrypting the original data using a preset encryption method;

[0020] The encrypted original data is sent to the data collector so that the data collector retains the original data whose data attributes meet the preset attribute requirements as valid data, wherein the data attributes include length and / or format.

[0021] On the other hand, before encrypting the original data using the preset encryption method, the data collection security guarantee method also includes:

[0022] For any original data to be sent, if there is a first type of preset label corresponding to the data type of the original data in the first corresponding relationship, determine the first type of preset label corresponding to the data type of the original data according to the first corresponding relationship;

[0023] The first type of preset label is set to the corresponding original data, so that the data collector determines the data type corresponding to the first type of preset label according to the first corresponding relationship.

[0024] On the other hand, before encrypting the original data using the preset encryption method, the data collection security guarantee method also includes:

[0025] Using a preset data feature extraction algorithm to extract data features of the original data, wherein the data features are used to characterize the inherent characteristics and patterns of the original data;

[0026] Grouping data features of the original data;

[0027] For any group of data features, a data feature model portrait is constructed according to each data feature in the group, wherein the data feature model portrait is used to present the feature distribution and correlation relationship of the original data involved in multiple dimensions;

[0028] For any of the data feature model portraits, determining a composite label corresponding to the data feature model portrait according to the second corresponding relationship;

[0029] The sub-tags constituting the composite tag are set one by one to the original data corresponding to the data feature model portrait, so that the data collector determines the data feature model portrait corresponding to the composite tag according to the second corresponding relationship;

[0030] The original data corresponding to the data feature model portrait refers to the original data corresponding to each data feature in the data feature group corresponding to the household feature model portrait.

[0031] On the other hand, before encrypting the original data using the preset encryption method, the data collection security guarantee method also includes:

[0032] The check value of the original data is calculated and stored so that the data receiver can determine the integrity of the original data based on the check value.

[0033] In order to solve the above technical problems, the present invention also provides a data acquisition security device, which is applied to a data collector and includes:

[0034] An acquisition module is used to acquire the encrypted original data sent by the data sender;

[0035] A judgment module, used for judging whether the data attribute of any of the original data meets the preset attribute requirement, and if so, triggering the action module, wherein the data attribute includes length and / or format;

[0036] The action module is used to retain the original data as valid data.

[0037] In order to solve the above technical problems, the present invention also provides a data collection security device, including:

[0038] Memory for storing computer programs;

[0039] A processor is used to implement the steps of the data collection security assurance method as described above when executing the computer program.

[0040] Beneficial effect: The present invention provides a data collection and filtering method. Considering that (1) some data attributes of the encrypted data will not change, and (2) some data types have specific data attributes, the data collector in the present invention can first obtain the encrypted original data sent by the data sender. For any original data, when the attribute data of the original data meets the preset attribute requirements, the original data is retained as valid data. Since "the data attributes meet the preset attribute requirements" indicates that the data type of the original data is "the data type corresponding to the preset attribute requirements", the present invention realizes the screening of data types through data attributes, realizes data collection and filtering on the basis of encryption, avoids the collected data from being leaked or tampered with, and improves the security of the collected data.

[0041] The present invention also provides a data acquisition and filtering device, equipment and computer-readable storage medium, which have the same beneficial effects as the above data acquisition and filtering method. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the relevant technologies and the drawings required for use in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 A schematic diagram of a flow chart of a data collection security assurance method provided by the present invention;

[0044] Figure 2 A schematic diagram of the configuration principle of data filtering provided by the present invention;

[0045] Figure 3 A schematic diagram of a data encryption process provided by the present invention;

[0046] Figure 4 A schematic diagram of a data decryption process provided by the present invention;

[0047] Figure 5 A schematic diagram of a data integrity check process provided by the present invention;

[0048] Figure 6A schematic diagram of the structure of a data collection security device provided by the present invention;

[0049] Figure 7 A schematic diagram of the structure of a data collection security device provided by the present invention. DETAILED DESCRIPTION

[0050] The core of the present invention is to provide a security guarantee method, device and equipment for data collection. The data collector can first obtain the encrypted original data sent by the data sender. For any original data, when the attribute data of the original data meets the preset attribute requirements, the original data is retained as valid data. Since "data attributes meet the preset attribute requirements" represents that the data type of the original data is "the data type corresponding to the preset attribute requirements", that is, the present invention realizes the screening of data types through data attributes, realizes data collection and filtering on the basis of encryption, avoids the collected data from being leaked or tampered with, and improves the security of the collected data.

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] Please refer to Figure 1 , Figure 1 A schematic flow chart of a data collection security assurance method provided by the present invention, wherein the data collection security assurance method is applied to a data collector, comprising:

[0053] S101: Obtaining the encrypted original data sent by the data sender;

[0054] Specifically, considering the technical problems in the above background technology, and considering that (1) certain data attributes of the encrypted data will not change, and (2) certain data types have specific data attributes, the embodiments of the present invention intend to screen the data through the data attributes of the encrypted original data, so as to determine the valid data and retain it. Therefore, the embodiments of the present invention can first obtain the encrypted original data sent by the data sender so as to use it as the data basis for subsequent steps.

[0055] Among them, the data sender and its corresponding original data can be of multiple types, for example, log data or device operation data, etc., and the fields to which the log data belongs can also be of multiple types, for example, it can be operation logs or transaction logs of cryptographic-related hardware (cryptographic devices, cryptographic systems, cryptographic service platforms) and other log data, etc. The embodiments of the present invention do not limit this.

[0056] S102: for any original data, determining whether data attributes of the original data meet preset attribute requirements, wherein the data attributes include length and / or format;

[0057] Specifically, based on the above considerations, that is, some data attributes of the encrypted original data can still reflect its data type. Therefore, the data collector in the embodiment of the present invention intends to determine the "encrypted original data" that meets the preset attribute requirements, so that when the original data is encrypted, it can still complete the data filtering work. Therefore, in this step, for any original data, it can be judged whether the data attributes of the original data meet the preset attribute requirements, and trigger subsequent actions based on the judgment results.

[0058] Specifically, in addition to the length and / or format, the data attributes may also be of other types, and the data attributes that need to be paid attention to in the original data are equal to the data attributes involved in the preset data attributes.

[0059] Among them, an example of a data attribute reflecting a data type may be that type A data (such as time data) has a specific data length (such as 6 bits), and type B data (such as location data) has a specific data format, which is not limited in the embodiment of the present invention.

[0060] The preset attribute requirements may be of various types, for example, a length of a certain number of specified bits (for example, 6 bits and 8 bits, etc.), a format of a certain number of specified formats, etc., which is not limited in the embodiment of the present invention.

[0061] S103: If satisfied, the original data is retained as valid data.

[0062] Specifically, if the data attributes meet the preset attribute requirements, it means that the original data belongs to the specific data type to be retained. Therefore, if it meets the requirements, the original data can be retained as valid data so as to be sent to the data recipient.

[0063] The present invention provides a data collection and filtering method. Considering that (1) some data attributes of encrypted data will not change, and (2) some data types have specific data attributes, the data collector in the present invention can first obtain the encrypted original data sent by the data sender. For any original data, when the attribute data of the original data meets the preset attribute requirements, the original data is retained as valid data. Since "the data attributes meet the preset attribute requirements" indicates that the data type of the original data is "the data type corresponding to the preset attribute requirements", the present invention realizes the screening of data types through data attributes, realizes data collection and filtering on the basis of encryption, avoids the collected data from being leaked or tampered with, and improves the security of the collected data.

[0064] Based on the above embodiments:

[0065] As an optional embodiment, for any original data, after determining whether the data attribute of the original data meets the preset attribute requirement, the data collection security assurance method further includes:

[0066] For any original data, determine whether the original data has a first type of preset label;

[0067] If so, the data type corresponding to the first type of preset label is determined according to the first corresponding relationship, and the original data and its corresponding data type are retained as valid data.

[0068] Specifically, considering that the labels on the original data can still be identified even when the original data is encrypted, in order to identify data of a specific data type, an embodiment of the present invention intends to identify data of a specific data type through a first type of preset label with the cooperation of the data sender. Before sending the original data, the data sender needs to set the first type of preset label for the original data in plain text, that is, through the first corresponding relationship (the corresponding relationship between the data type and the first type of preset label), the original data of the data type involved is marked with the corresponding first type of preset label, and then the original data is encrypted and sent to the data collector. In this way, the data collector can determine the data type corresponding to the first type of preset label for the original data with the first type of preset label according to the first corresponding relationship, and retain the original data and its corresponding data type as valid data.

[0069] Specifically, retaining the original data and its corresponding data type as valid data refers to binding the original data and its corresponding data type to identify the data type of the original data. For example, the original data and its corresponding data type can be stored in Json format, and the storage form is "data type: ciphertext original data".

[0070] Specifically, the first corresponding relationship can be set independently, and each data type involved in the first corresponding relationship can also be set independently according to the application scenario, which is not limited in the embodiment of the present invention.

[0071] As an optional embodiment, after obtaining the encrypted original data sent by the data sender, the data collection security assurance method further includes:

[0072] Determine whether there is a composite label in the original data, where a composite label refers to a label composed of sub-labels on multiple original data;

[0073] If it exists, determine the data feature model portrait corresponding to the composite label according to the second corresponding relationship;

[0074] The data feature model portrait and its corresponding original data are retained together as valid data, wherein the original data corresponding to the data feature model portrait refers to the original data of each sub-label of the composite label corresponding to the data feature model portrait.

[0075] Specifically, considering that the feature model portrait of data can extract, analyze and combine various features of data to construct a model description that can represent the typical features of the data subject (such as users, products, events, etc.). It is like a detailed "portrait" of the data subject, which is used to better understand, classify and predict the behavior or attributes of the subject. The composite label composed of multiple sub-labels of the original data can represent the specific data feature model fantasy corresponding to these original data. Therefore, in the embodiment of the present invention, it can be further coordinated with the data sender, that is, before the data sender encrypts the original data, it can determine the data feature model portrait corresponding to each group of original data, and set the corresponding sub-labels of the composite label corresponding to the data feature model portrait to these original data one by one, and then encrypt these original data. Then, the data collector can first determine the composite label through the sub-labels of the original data, and then determine the data feature model portrait corresponding to the composite label through the second corresponding relationship (that is, the corresponding relationship between the composite label and the data feature model portrait), and finally the data feature model portrait and its corresponding original data can be retained as valid data.

[0076] Among them, there can be many specific ways to retain the data feature model portrait and its corresponding original data as valid data. For example, the data feature model portrait and its corresponding original data can be bound, for example, and stored in Json format. The embodiment of the present invention is not limited here.

[0077] Specifically, in order to better illustrate the embodiments of the present invention, please refer to Figure 2 , Figure 2 A schematic diagram of the configuration principle of data filtering provided by the present invention shows the configuration principle of the data collector's filtering rules for ciphertext data, including: the encrypted data and the original data maintain the same data length, the encrypted data and the original data maintain the same data format, the encrypted data reflects the data type of the original data through a label, and the encrypted data reflects the data feature model portrait through a composite label.

[0078] As an optional embodiment, the data collection security assurance method further includes:

[0079] In response to the modification instruction, the first corresponding relationship and / or the second corresponding relationship is modified.

[0080] Specifically, considering that there may be a need for flexible modification of the first correspondence relationship and the second correspondence relationship, in order to facilitate the change of filtering specifications, an embodiment of the present invention provides a correspondence modification interface, that is, the first correspondence relationship and / or the second correspondence relationship can be modified in response to a modification instruction, thereby improving the flexibility of data filtering.

[0081] In order to solve the above technical problems, the present invention also provides a data collection security guarantee method, which is applied to the data sender, comprising:

[0082] Encrypting the original data using a preset encryption method;

[0083] The encrypted original data is sent to the data collector so that the data collector retains the original data whose data attributes meet the preset attribute requirements as valid data, wherein the data attributes include length and / or format.

[0084] Specifically, considering that the relevant technology lacks a filtering method for the encrypted original data, the data sent by the data sender are all plain text data, and the data security is poor. On the basis of having a filtering method for the encrypted original data, the data sender can also encrypt the original data and then send the data, thereby improving data security.

[0085] To better illustrate the embodiments of the present invention, please refer to Figure 3 and Figure 4 , Figure 3 A schematic diagram of a data encryption process provided by the present invention, Figure 4A schematic diagram of a data decryption process provided by the present invention, taking log data as an example, firstly (using a random key) the log data is symmetrically encrypted using a national secret algorithm to obtain data ciphertext, and the symmetrically encrypted random key is asymmetrically encrypted using the receiver's public key (that is, the data receiver's public key) to obtain key ciphertext, and then the data ciphertext and the key ciphertext are combined into a ciphertext data packet and sent to a data collector, and the ciphertext data packet can be transmitted to the data receiver through the data collector. Figure 4 In the data decryption process for the data recipient, for the key ciphertext, the recipient's private key can be used to perform asymmetric decryption to obtain a symmetric encrypted random key, and then the random key can be used to symmetric decrypt the data ciphertext to obtain the data plaintext.

[0086] As an optional embodiment, before encrypting the original data using the preset encryption method, the data collection security guarantee method further includes:

[0087] For any original data to be sent, if there is a first type of preset label corresponding to the data type of the original data in the first corresponding relationship, determine the first type of preset label corresponding to the data type of the original data according to the first corresponding relationship;

[0088] The first type of preset label is set to the corresponding original data, so that the data collector determines the data type corresponding to the first type of preset label according to the first corresponding relationship.

[0089] Specifically, in order to enable the data collector to determine the data type of the original data through the first type of preset label in the encrypted original data, the data sender in the embodiment of the present invention can set the first type of preset label for the original data in plain text before encryption.

[0090] As an optional embodiment, before encrypting the original data using the preset encryption method, the data collection security guarantee method further includes:

[0091] A preset data feature extraction algorithm is used to extract data features of the original data, wherein the data features are used to characterize the inherent characteristics and patterns of the original data;

[0092] Grouping data features of raw data;

[0093] For any group of data features, a data feature model portrait is constructed based on each data feature in the group, wherein the data feature model portrait is used to present the feature distribution and correlation relationship of the original data involved in multiple dimensions;

[0094] For any data feature model portrait, determine a composite label corresponding to the data feature model portrait according to the second corresponding relationship;

[0095] The sub-tags constituting the composite tag are set one by one to the original data corresponding to the data feature model portrait, so that the data collector determines the data feature model portrait corresponding to the composite tag according to the second corresponding relationship;

[0096] The original data corresponding to the data feature model portrait refers to the original data corresponding to each data feature in the data feature group corresponding to the household feature model portrait.

[0097] Specifically, in order to enable the data collector to determine the data feature model portrait of each group of original data through the composite label, the data sender in the embodiment of the present invention can determine the data feature model portrait of each group of original data before encrypting the original data, and convert it into a composite label composed of various sub-labels through a second corresponding relationship, and set it on the group of original data.

[0098] Among them, the original data comes from "specific original data sources, such as specific sensor networks, database systems or data acquisition equipment, etc." The original data can also be preprocessed. The preprocessing operation can include data cleaning steps to remove noise data, abnormal data and duplicate data in the original data, and can also include data standardization steps to convert data of different formats and magnitudes into a unified standard format and a suitable magnitude range; then, data feature extraction is performed based on the preprocessed original data. The extraction process can adopt a variety of methods (such as principal component analysis algorithm, feature extraction network in deep learning, etc.) to identify and extract key data features that can effectively characterize the inherent characteristics and patterns of the original data; then, after the extracted data features are grouped, for any group of data features, the extracted data features are used to construct a data feature model portrait. The data feature model portrait organizes and integrates the extracted data features in a specific structural way to intuitively and systematically present the feature distribution and correlation relationship of the original data in multiple dimensions (such as time dimension, space dimension, numerical attribute dimension, etc.), thereby providing an accurate and highly representative data foundation for subsequent data analysis, decision making or target application (such as risk assessment, user behavior prediction, etc.) based on the data feature model portrait.

[0099] Specifically, the process of constructing a data feature model portrait using the log data of a password service platform as an example can be as follows:

[0100] (1) Data collection:

[0101] First, log data is collected from various components and interfaces of the password service platform. The sources of these log data may include user authentication modules, password encryption / decryption modules, key management modules, etc. For example, the log of the user authentication module may record the time of user login, IP address, authentication success or failure information; the log of the password encryption / decryption module may contain data such as the time of encryption / decryption operation, the algorithm used, and whether the operation was successful.

[0102] (2) Data preprocessing:

[0103] Data cleaning: Remove irrelevant information from log data, such as debugging information, duplicate records, etc. For example, some logs generated by temporary print statements during the development process may not be valuable for portrait construction and need to be deleted. At the same time, clean up erroneous or incomplete log records.

[0104] Data format standardization: Unify the formats of log data from different sources. For example, the timestamp format may vary from module to module, and it needs to be unified into a standard format, such as "YYYY-MM-DDHH:MM:SS", for subsequent processing.

[0105] (3) Data feature extraction:

[0106] Basic feature extraction:

[0107] Time features: Extract time-related features of log records, such as date, hour, minute, etc., to analyze the peak and trough periods of password service platform usage. For example, it is found that 8-10 pm every day is the peak period for users to log in and use the password service.

[0108] User-related features: Extract information such as user ID, user role, and user organization from the log. If the log contains the user's IP address, the IP address can also be converted into geographic location information through the geographic location database to analyze the use of the password service platform by users in different regions.

[0109] Operation-related features: Extract operation types (such as authentication operations, password modification operations, encryption operations, etc.), operation results (success or failure), etc. For example, by counting the success rate of each operation type, it is found that the success rate of password modification operations is 95%, while the success rate of authentication operations is 90%.

[0110] Correlation feature extraction:

[0111] Operation sequence characteristics: Analyze the user's operation sequence on the password service platform. For example, it is found that the probability of a user changing the password immediately after successfully logging in is 10%. This operation sequence feature can help identify potential abnormal behavior patterns.

[0112] User-operation correlation characteristics: Analyze the correlation between different user roles and operation types. For example, administrator users perform more key management operations, while ordinary users mainly perform password encryption / decryption operations.

[0113] (3) Data feature grouping and integration:

[0114] The extracted data features are grouped, for example, time features are grouped into one group, user features are grouped into one group, and operation features are grouped into one group. Within each group, the relationship between features is further analyzed. Then, these grouped features are integrated together to build a complete data feature model portrait.

[0115] For example, a three-dimensional data feature model portrait is constructed that includes the "time dimension" (peak usage period and trough period), "user dimension" (user role, geographical location distribution) and "operation dimension" (operation type distribution, operation success rate, operation sequence) to comprehensively describe the characteristics of the cryptographic service platform log data.

[0116] (4) Model portrait verification and optimization:

[0117] Use a portion of known, labeled log data (such as normal or abnormal operation logs) to verify the accuracy of the constructed data feature model portrait. If it is found that the model portrait cannot well identify abnormal behavior or accurately describe the platform usage, it is necessary to optimize the feature extraction method or grouping method.

[0118] For example, by comparing actual abnormal events with abnormal situations predicted by model portraits, it is found that the model portraits have missed some key operation sequence features, resulting in a low abnormal behavior recognition rate. At this time, it is necessary to readjust the feature extraction strategy and add these omitted features to the model portraits.

[0119] As an optional embodiment, before encrypting the original data using the preset encryption method, the data collection security guarantee method further includes:

[0120] Calculate and store the checksum of the original data so that the data receiver can determine the integrity of the original data based on the checksum.

[0121] Specifically, considering that the data integrity of the encrypted original data may still be damaged during the transmission process, in order to further ensure data security, the data sender in the embodiment of the present invention can calculate and store the verification value of the original data so that the data receiver can determine the integrity of the original data based on the verification value.

[0122] The verification algorithm used to calculate the verification value may be of various types, such as CMAC (Cipher-based Message Authentication Code), etc., which is not limited in the embodiment of the present invention.

[0123] Specifically, in order to further improve data security, taking log data as the original data, the combination of the log key and the key information of the log can also be used to calculate the check value. For better explanation of the embodiment of the present invention, please refer to Figure 5 , Figure 5 A flow chart of data integrity verification provided by the present invention is provided. The application server can be regarded as a data receiver. The verification value calculated by the data sender is stored in a database. For the received log data, the application server can extract the key information of the log (which can be set independently) and encapsulate it as Log Info. At the same time, the ciphertext of the log key Keylog can be obtained from the key file, and the ciphertext of Keylog can be decrypted (through the password module) to obtain the log key Keylog. Then, CMAC calculation can be performed on the combination of the log key and the key information of the log, that is, CMAC (Keylog, Log Info) is calculated. Then, the database and the newly calculated CMAC can be compared. If the two are consistent, it means that the log data is complete. If the two are inconsistent, it means that the log integrity is destroyed.

[0124] Please refer to Figure 6 , Figure 6 This is a schematic diagram of the structure of a data acquisition security device provided by the present invention, which is applied to a data collector and includes:

[0125] An acquisition module 61 is used to acquire the encrypted original data sent by the data sender;

[0126] The judgment module 62 is used to judge whether the data attribute of any original data meets the preset attribute requirements, and if so, trigger the action module, wherein the data attribute includes length and / or format;

[0127] The action module 63 is used to retain the original data as valid data.

[0128] For an introduction to the data collection security assurance device provided in the embodiment of the present invention, please refer to the embodiment of the data collection security assurance method described above, and the embodiment of the present invention will not be described in detail here.

[0129] Please refer to Figure 7 , Figure 7A schematic diagram of a data collection security device provided by the present invention, wherein the data collection security device comprises:

[0130] A memory 71, used for storing computer programs;

[0131] The processor 72 is used to implement the steps of the data collection security assurance method in the above-mentioned embodiment when executing the computer program.

[0132] For an introduction to the data collection security assurance device provided in the embodiment of the present invention, please refer to the aforementioned embodiment of the data collection security assurance method, and the embodiment of the present invention will not be described in detail here.

[0133] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should also be noted that in this specification, 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 that there is any such actual relationship or order between these entities or operations. Moreover, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements that are not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or equipment including the element.

[0134] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. 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 invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A data collection security method, characterized in that: Applicable to data loggers, including: Obtain the encrypted original data sent by the data sender; For any of the original data, determining whether data attributes of the original data meet preset attribute requirements, wherein the data attributes include length and / or format; If satisfied, the original data is retained as valid data.

2. The data collection security method according to claim 1, characterized in that: After determining, for any of the original data, whether the data attribute of the original data meets the preset attribute requirement, the data collection security assurance method further includes: For any of the original data, determining whether the original data has a first type of preset label; If so, the data type corresponding to the first type of preset label is determined according to the first corresponding relationship, and the original data and its corresponding data type are retained as valid data.

3. The data collection security method according to any one of claims 1 to 2, characterized in that: After obtaining the encrypted original data sent by the data sender, the data collection security guarantee method further includes: Determine whether there is a composite tag in the original data, wherein the composite tag refers to a tag composed of sub-tags on multiple original data; If so, determining the data feature model portrait corresponding to the composite tag according to the second corresponding relationship; The data feature model portrait and its corresponding original data are retained together as valid data, wherein the original data corresponding to the data feature model portrait refers to the original data of each sub-label of the composite label corresponding to the data feature model portrait.

4. The data collection security method according to claim 2, characterized in that: The data collection security guarantee method also includes: In response to the modification instruction, the first corresponding relationship and / or the second corresponding relationship is modified.

5. A data collection security method, characterized in that: Applicable to data senders, including: Encrypting the original data using a preset encryption method; The encrypted original data is sent to the data collector so that the data collector retains the original data whose data attributes meet the preset attribute requirements as valid data, wherein the data attributes include length and / or format.

6. The data collection security method according to claim 5, characterized in that: Before encrypting the original data using the preset encryption method, the data collection security guarantee method also includes: For any original data to be sent, if there is a first type of preset label corresponding to the data type of the original data in the first corresponding relationship, determine the first type of preset label corresponding to the data type of the original data according to the first corresponding relationship; The first type of preset label is set to the corresponding original data, so that the data collector determines the data type corresponding to the first type of preset label according to the first corresponding relationship.

7. The data collection security method according to claim 5 or 6, characterized in that: Before encrypting the original data using the preset encryption method, the data collection security guarantee method also includes: Using a preset data feature extraction algorithm to extract data features of the original data, wherein the data features are used to characterize the inherent characteristics and patterns of the original data; Grouping data features of the original data; For any group of data features, a data feature model portrait is constructed according to each data feature in the group, wherein the data feature model portrait is used to present the feature distribution and correlation relationship of the original data involved in multiple dimensions; For any of the data feature model portraits, determining a composite label corresponding to the data feature model portrait according to the second corresponding relationship; The sub-tags constituting the composite tag are set one by one to the original data corresponding to the data feature model portrait, so that the data collector determines the data feature model portrait corresponding to the composite tag according to the second corresponding relationship; The original data corresponding to the data feature model portrait refers to the original data corresponding to each data feature in the data feature group corresponding to the household feature model portrait.

8. The data collection security method according to claim 5, characterized in that: Before encrypting the original data using the preset encryption method, the data collection security guarantee method also includes: The check value of the original data is calculated and stored so that the data receiver can determine the integrity of the original data based on the check value.

9. A data collection security device, characterized in that: Applicable to data loggers, including: An acquisition module is used to acquire the encrypted original data sent by the data sender; A judgment module, used for judging whether the data attribute of any of the original data meets the preset attribute requirements, and if so, triggering the action module, wherein the data attribute includes length and / or format; The action module is used to retain the original data as valid data.

10. A data collection security device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the data collection security assurance method as claimed in any one of claims 1 to 8 when executing the computer program.

Images