Data security transmission method and system based on structured tags

Abstract

The present invention discloses a data security transmission method and system based on structured tags, the method comprising: obtaining home data to be transmitted and corresponding device information; identifying multiple sensitive data parts and corresponding sensitivity levels in the home data according to a sensitive identification algorithm model corresponding to the device information; encrypting each of the sensitive data parts according to a public key corresponding to the sensitivity level to obtain an encrypted data part; combining all the encrypted data parts and the corresponding private key information based on a structured tag algorithm to obtain encrypted home data for transmission; after being received, the encrypted home data can be decrypted based on a preset structured identification rule and a corresponding private key to obtain the home data. It can be seen that the present invention can improve the pertinence and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a data security transmission method and system based on structured tags. Background Art

[0002] With the development of smart home technology and the increasing demand for smart furniture, more and more smart devices have appeared in people's home environments. During operation, these smart home devices will inevitably transmit a large amount of data in the home environment, such as sending or receiving instructions or transmitting and warning specific data obtained by monitoring. When solving the problem of secure data transmission of home appliances, most of the existing technologies only rely on general encryption algorithms to achieve secure data transmission, and do not effectively combine data structure annotation with structured tags to identify and encrypt data of different sensitivity levels. Therefore, the security of data transmission is not high enough and the protection effect is not good enough. It can be seen that the existing technology has defects that need to be solved urgently. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a data security transmission method and system based on structured tags, which can improve the pertinence and reliability of home data encryption, reduce encryption costs, and improve data transmission security.

[0004] In order to solve the above technical problems, the first aspect of the present invention discloses a data security transmission method based on structured tags, the method comprising:

[0005] Obtaining home data to be transmitted and corresponding device information;

[0006] According to the sensitive identification algorithm model corresponding to the device information, multiple sensitive data parts and corresponding sensitivity levels in the home data are identified;

[0007] Encrypting each of the sensitive data parts according to the public key corresponding to the sensitivity to obtain an encrypted data part;

[0008] All the encrypted data parts and the corresponding private key information are combined based on the structured label algorithm to obtain the encrypted home data for transmission; after being received, the encrypted home data can be decrypted based on the preset structured recognition rules and the corresponding private key to obtain the home data.

[0009] As an optional implementation, in the first aspect of the present invention, the identifying multiple sensitive data parts and corresponding sensitivity levels in the home data according to the sensitive identification algorithm model corresponding to the device information includes:

[0010] Determining a target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information;

[0011] Input each data portion of the household data into the target sensitivity recognition algorithm model to obtain the sensitivity type and prediction probability corresponding to each data portion;

[0012] According to the sensitivity type and the predicted probability, a plurality of sensitive data parts and corresponding sensitivity levels are screened out from all the data parts.

[0013] As an optional implementation, in the first aspect of the present invention, determining the target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information includes:

[0014] For each candidate model, obtain a set of all prediction sensitive types in the historical prediction results corresponding to the candidate model to obtain prediction result data;

[0015] Determine the possible sensitive type corresponding to the device information according to the preset correspondence between the device information and the sensitive type;

[0016] Calculating the type similarity between the possible sensitive type and the prediction result data to obtain a similarity parameter of the candidate model;

[0017] The candidate model with the highest similarity parameter is determined as the target sensitive recognition algorithm model; the target sensitive recognition algorithm model is trained by a training data set including a plurality of training home data and corresponding sensitive type annotations of different data parts.

[0018] As an optional implementation, in the first aspect of the present invention, the screening out multiple sensitive data parts and corresponding sensitivity levels from all the data parts according to the sensitivity type and the predicted probability includes:

[0019] For each of the data parts, determining a sensitivity score corresponding to the data part according to the sensitivity type corresponding to the data part and a preset scoring rule for the sensitivity type;

[0020] Calculating a weighted average of the sensitivity score and the predicted probability to obtain a comprehensive sensitivity probability corresponding to the data portion;

[0021] Determine all the data parts whose comprehensive sensitivity probability is higher than a preset probability threshold as sensitive data parts;

[0022] The comprehensive sensitivity probability corresponding to each of the sensitive data parts is determined as its corresponding sensitivity level.

[0023] As an optional implementation, in the first aspect of the present invention, encrypting each of the sensitive data parts according to the public key corresponding to the sensitivity to obtain the encrypted data part includes:

[0024] Determine a target key library from a plurality of preset key libraries according to the device information; the device information includes device information of a sending device and a receiving device; the target key library includes a plurality of encryption algorithms and key pairs that have been determined by the sending device and the receiving device through communication;

[0025] For each of the sensitive data parts, determining a target algorithm and a target key pair in the target key library according to the sensitivity corresponding to the sensitive data part;

[0026] The sensitive data portion is encrypted according to the target algorithm and the public key in the target key pair to obtain an encrypted data portion.

[0027] As an optional implementation, in the first aspect of the present invention, determining a target algorithm and a target key pair in the target key library according to the sensitivity corresponding to the sensitive data portion includes:

[0028] Determine the encryption algorithm type corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the correspondence between the preset sensitivity level and the encryption algorithm type;

[0029] Determine the key length corresponding to the sensitive data portion according to the sensitivity corresponding to the sensitive data portion and the corresponding relationship between the preset sensitivity and the key length;

[0030] A target algorithm and a target key pair are determined in the target key library according to the encryption algorithm type and the key length.

[0031] As an optional implementation, in the first aspect of the present invention, all the encrypted data parts and the corresponding private key information are combined based on a structured labeling algorithm to obtain encrypted home data, including:

[0032] Generate a tag structure portion corresponding to each of the encrypted data portions based on a structured tag algorithm;

[0033] For each of the label structure parts, a private key feature identifier corresponding to the private key in the target key pair corresponding to the encrypted data part corresponding to the label structure part is marked in the label structure part to obtain a corresponding marked label structure;

[0034] All the annotated tag structures and other unencrypted data parts are combined based on a preset combination order to obtain encrypted home data.

[0035] As an optional implementation, in the first aspect of the present invention, the structured tagging algorithm is an XML format algorithm, an HTML format algorithm, a YAML format algorithm or a JSON format algorithm.

[0036] A second aspect of an embodiment of the present invention discloses a data security transmission system based on structured tags, the system comprising:

[0037] An acquisition module, used to acquire home data to be transmitted and corresponding device information;

[0038] an identification module, configured to identify multiple sensitive data parts and corresponding sensitivity levels in the home data according to a sensitive identification algorithm model corresponding to the device information;

[0039] An encryption module, used for encrypting each of the sensitive data parts according to the public key corresponding to the sensitivity to obtain an encrypted data part;

[0040] A combination module is used to combine all the encrypted data parts and the corresponding private key information based on a structured label algorithm to obtain encrypted home data for transmission; after being received, the encrypted home data can be decrypted based on a preset structured recognition rule and the corresponding private key to obtain the home data.

[0041] As an optional implementation, in the second aspect of the present invention, the identification module identifies multiple sensitive data parts and corresponding sensitivity levels in the home data according to the sensitive identification algorithm model corresponding to the device information, including:

[0042] Determining a target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information;

[0043] Input each data portion of the household data into the target sensitivity recognition algorithm model to obtain the sensitivity type and prediction probability corresponding to each data portion;

[0044] According to the sensitivity type and the predicted probability, a plurality of sensitive data parts and corresponding sensitivity levels are screened out from all the data parts.

[0045] As an optional implementation, in the second aspect of the present invention, the specific manner in which the recognition module determines the target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information includes:

[0046] For each candidate model, obtain a set of all prediction sensitive types in the historical prediction results corresponding to the candidate model to obtain prediction result data;

[0047] Determine the possible sensitive type corresponding to the device information according to the preset correspondence between the device information and the sensitive type;

[0048] Calculating the type similarity between the possible sensitive type and the prediction result data to obtain a similarity parameter of the candidate model;

[0049] The candidate model with the highest similarity parameter is determined as the target sensitive recognition algorithm model; the target sensitive recognition algorithm model is trained by a training data set including a plurality of training home data and corresponding sensitive type annotations of different data parts.

[0050] As an optional implementation, in the second aspect of the present invention, the specific manner in which the identification module selects multiple sensitive data parts and corresponding sensitivity levels from all the data parts according to the sensitivity type and the predicted probability includes:

[0051] For each of the data parts, determining a sensitivity score corresponding to the data part according to the sensitivity type corresponding to the data part and a preset scoring rule for the sensitivity type;

[0052] Calculating a weighted average of the sensitivity score and the predicted probability to obtain a comprehensive sensitivity probability corresponding to the data portion;

[0053] Determine all the data parts whose comprehensive sensitivity probability is higher than a preset probability threshold as sensitive data parts;

[0054] The comprehensive sensitivity probability corresponding to each of the sensitive data parts is determined as its corresponding sensitivity level.

[0055] As an optional implementation, in the second aspect of the present invention, the encryption module encrypts each of the sensitive data parts according to the public key corresponding to the sensitivity to obtain the encrypted data part in a specific manner, including:

[0056] Determine a target key library from a plurality of preset key libraries according to the device information; the device information includes device information of a sending device and a receiving device; the target key library includes a plurality of encryption algorithms and key pairs that have been determined by the sending device and the receiving device through communication;

[0057] For each of the sensitive data parts, determining a target algorithm and a target key pair in the target key library according to the sensitivity corresponding to the sensitive data part;

[0058] The sensitive data portion is encrypted according to the target algorithm and the public key in the target key pair to obtain an encrypted data portion.

[0059] As an optional implementation, in the second aspect of the present invention, the encryption module determines the specific manner of the target algorithm and the target key pair in the target key library according to the sensitivity corresponding to the sensitive data portion, including:

[0060] Determine the encryption algorithm type corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the correspondence between the preset sensitivity level and the encryption algorithm type;

[0061] Determine the key length corresponding to the sensitive data portion according to the sensitivity corresponding to the sensitive data portion and the corresponding relationship between the preset sensitivity and the key length;

[0062] A target algorithm and a target key pair are determined in the target key library according to the encryption algorithm type and the key length.

[0063] As an optional implementation, in the second aspect of the present invention, the specific manner in which the combination module combines all the encrypted data parts and the corresponding private key information based on the structured label algorithm to obtain the encrypted home data includes:

[0064] Generate a tag structure portion corresponding to each of the encrypted data portions based on a structured tag algorithm;

[0065] For each of the label structure parts, a private key feature identifier corresponding to the private key in the target key pair corresponding to the encrypted data part corresponding to the label structure part is marked in the label structure part to obtain a corresponding marked label structure;

[0066] All the annotated tag structures and other unencrypted data parts are combined based on a preset combination order to obtain encrypted home data.

[0067] As an optional implementation, in the second aspect of the present invention, the structured tagging algorithm is an XML format algorithm, an HTML format algorithm, a YAML format algorithm or a JSON format algorithm.

[0068] The third aspect of the present invention discloses another data security transmission system based on structured tags, the system comprising:

[0069] A memory storing executable program code;

[0070] a processor coupled to the memory;

[0071] The processor calls the executable program code stored in the memory to execute part or all of the steps in the data security transmission method based on structured tags disclosed in the first aspect of the present invention.

[0072] The fourth aspect of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all of the steps in the data security transmission method based on structured tags disclosed in the first aspect of the present invention.

[0073] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0074] The present invention can identify multiple sensitive data parts in home data based on the sensitive identification algorithm model corresponding to the backup information, and then encrypt each sensitive data part based on the public key corresponding to the sensitivity to obtain an encrypted data part, and finally transmit the encrypted home data according to the structured label algorithm combination, thereby improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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.

[0076] Figure 1 It is a flow chart of a data security transmission method based on structured tags disclosed in an embodiment of the present invention.

[0077] Figure 2 It is a structural schematic diagram of a data security transmission system based on structured tags disclosed in an embodiment of the present invention.

[0078] Figure 3 It is a structural schematic diagram of another data security transmission system based on structured tags disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0079] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 only 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.

[0080] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or equipment that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or equipment.

[0081] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0082] The present invention discloses a data security transmission method and system based on structured tags, which can identify multiple sensitive data parts in home data based on a sensitive identification algorithm model corresponding to backup information, and then encrypt each sensitive data part based on a public key corresponding to the sensitivity to obtain an encrypted data part, and finally transmit the encrypted home data obtained according to the structured tag algorithm combination, thereby improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security. The following are detailed descriptions.

[0083] Embodiment 1

[0084] See also Figure 1 , Figure 1 : is a flow chart of a data security transmission method based on structured tags disclosed in an embodiment of the present invention. Figure 1 The structured tag-based data security transmission method described above can be applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 1 As shown, the data security transmission method based on structured tags may include the following operations:

[0085] 101. Obtain home data to be transmitted and corresponding device information.

[0086] 102. According to the sensitive identification algorithm model corresponding to the device information, multiple sensitive data parts and corresponding sensitivity levels in the home data are identified.

[0087] 103. Encrypt each sensitive data portion according to the public key corresponding to the sensitivity to obtain an encrypted data portion.

[0088] 104. All encrypted data parts and corresponding private key information are combined based on the structured label algorithm to obtain encrypted home data for transmission.

[0089] Optionally, after being received, the encrypted home data can be decrypted based on a preset structured recognition rule and a corresponding private key to obtain the home data.

[0090] It can be seen that the above-mentioned invention embodiment can identify multiple sensitive data parts in the home data based on the sensitive identification algorithm model corresponding to the backup information, and then encrypt each sensitive data part based on the public key corresponding to the sensitivity to obtain an encrypted data part, and finally transmit the encrypted home data according to the structured label algorithm combination, thereby improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0091] As an optional embodiment, in the above steps, according to the sensitive identification algorithm model corresponding to the device information, multiple sensitive data parts and corresponding sensitivity levels in the home data are identified, including:

[0092] Determine a target sensitive recognition algorithm model from a plurality of preset candidate models according to device information;

[0093] Input each data part of the household data into the target sensitive identification algorithm model to obtain the sensitive type and prediction probability corresponding to each data part;

[0094] According to the sensitivity type and predicted probability, multiple sensitive data parts and corresponding sensitivity levels are screened out from all data parts.

[0095] It can be seen that through the above-mentioned optional embodiments, the target sensitive identification algorithm model can be determined from the preset multiple candidate models based on the device information to predict the sensitivity type and prediction probability corresponding to each data part, and further screen out multiple sensitive data parts and corresponding sensitivity levels, so as to facilitate subsequent data encryption and combination, and assist in improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0096] As an optional embodiment, in the above step, determining the target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information includes:

[0097] For each candidate model, obtain a set of all prediction sensitive types in the historical prediction results corresponding to the candidate model to obtain prediction result data;

[0098] Determine the possible sensitive type corresponding to the device information according to the preset correspondence between the device information and the sensitive type;

[0099] Calculate the type similarity between the possible sensitive type and the predicted result data to obtain the similarity parameter of the candidate model;

[0100] The candidate model with the highest similarity parameter is determined as the target sensitive recognition algorithm model; the target sensitive recognition algorithm model is trained by a training data set including multiple training home data and corresponding sensitive type annotations of different data parts.

[0101] It can be seen that through the above-mentioned optional embodiments, it is possible to screen a suitable prediction model based on the similarity between the prediction type in the historical prediction results of the candidate model and the possible type corresponding to the device information, so as to facilitate the subsequent prediction of sensitive types, and subsequently realize data encryption and combination, so as to assist in improving the pertinence and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

[0102] As an optional embodiment, in the above step, multiple sensitive data parts and corresponding sensitivity levels are screened out from all data parts according to the sensitivity type and the predicted probability, including:

[0103] For each data portion, determine the sensitivity score corresponding to the data portion according to the sensitivity type corresponding to the data portion and the preset scoring rule of the sensitivity type;

[0104] Calculate the weighted average of the sensitivity score and the predicted probability to obtain the comprehensive sensitivity probability corresponding to the data portion;

[0105] Determine all data parts whose comprehensive sensitivity probability is higher than a preset probability threshold as sensitive data parts;

[0106] The comprehensive sensitivity probability corresponding to each sensitive data part is determined as its corresponding sensitivity level.

[0107] It can be seen that through the above-mentioned optional embodiments, the sensitivity probability of the data part can be comprehensively determined based on the score of the sensitive type and the prediction probability of the model, so as to screen and determine the sensitivity of specific data parts with high sensitivity and high prediction probability, which is convenient for subsequent data encryption and combination, and helps to improve the targeting and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

[0108] As an optional embodiment, in the above steps, encrypting each sensitive data part according to the public key corresponding to the sensitivity to obtain the encrypted data part includes:

[0109] Determine a target key library from a plurality of preset key libraries according to the device information; optionally, the device information includes device information of a sending device and a receiving device; the target key library includes encryption algorithms and key pairs that have been determined by the sending device and the receiving device through communication;

[0110] For each sensitive data portion, determining a target algorithm and a target key pair in a target key library according to the sensitivity level corresponding to the sensitive data portion;

[0111] According to the target algorithm and the public key in the target key pair, the sensitive data portion is encrypted to obtain the encrypted data portion.

[0112] It can be seen that through the above-mentioned optional embodiments, the target key library can be determined in the preset multiple key libraries based on the device information, and then the target algorithm and target key pair can be determined in the target key library according to the sensitivity level corresponding to the sensitive data part to realize the encryption of the data part, which is convenient for subsequent data combination and secure transmission, and helps to improve the pertinence and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

[0113] As an optional embodiment, in the above steps, determining the target algorithm and the target key pair in the target key library according to the sensitivity corresponding to the sensitive data portion includes:

[0114] Determine the encryption algorithm type corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the correspondence between the preset sensitivity level and the encryption algorithm type;

[0115] Determine the key length corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the corresponding relationship between the preset sensitivity level and the key length;

[0116] The target algorithm and the target key pair are determined in the target key library according to the encryption algorithm type and the key length.

[0117] It can be seen that through the above-mentioned optional embodiments, the corresponding encryption algorithm type and key length can be determined based on the corresponding relationship between the preset sensitivity and the algorithm type or key length, and the target algorithm and target key pair can be determined in the target key library to realize encryption of the data part, which is convenient for subsequent data combination and secure transmission, and assists in improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0118] As an optional embodiment, in the above steps, all encrypted data parts and corresponding private key information are combined based on a structured label algorithm to obtain encrypted home data, including:

[0119] Generate a label structure portion corresponding to each encrypted data portion based on a structured label algorithm;

[0120] For each label structure part, a private key feature identifier corresponding to a private key in a target key pair corresponding to an encrypted data part corresponding to the label structure part is annotated in the label structure part to obtain a corresponding annotated label structure;

[0121] All the annotated label structures and other unencrypted data parts are combined based on a preset combination order to obtain the encrypted home data.

[0122] It can be seen that through the above-mentioned optional embodiments, the label structure part corresponding to each encrypted data part can be generated based on the structured label algorithm, and then marked according to the corresponding private key feature identifier to combine and obtain the encrypted home data, which is convenient for subsequent data security transmission, thereby improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0123] As an optional embodiment, in the above steps, the structured tag algorithm is an XML format algorithm, an HTML format algorithm, a YAML format algorithm or a JSON format algorithm.

[0124] It can be seen that through the above optional embodiments, the type of structured labeling algorithm is limited to efficiently implement data structuring and labeling operations, facilitate subsequent data security transmission, improve the pertinence and reliability of home data encryption, reduce encryption costs, and improve data transmission security.

[0125] Embodiment 2

[0126] See also Figure 2 , Figure 2 : is a schematic diagram of a data security transmission system based on structured tags disclosed in an embodiment of the present invention. Figure 2 The structured tag-based data security transmission system described above can be applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 2 As shown, the data security transmission system based on structured tags may include:

[0127] The acquisition module 201 is used to acquire the home data to be transmitted and the corresponding device information.

[0128] The identification module 202 is used to identify multiple sensitive data parts and corresponding sensitivity levels in the home data according to the sensitive identification algorithm model corresponding to the device information.

[0129] The encryption module 203 is used to encrypt each sensitive data part according to the public key corresponding to the sensitivity to obtain an encrypted data part.

[0130] The combining module 204 is used to combine all encrypted data parts and corresponding private key information based on the structured label algorithm to obtain encrypted home data for transmission.

[0131] Optionally, after being received, the encrypted home data can be decrypted based on a preset structured recognition rule and a corresponding private key to obtain the home data.

[0132] It can be seen that the above-mentioned invention embodiment can identify multiple sensitive data parts in the home data based on the sensitive identification algorithm model corresponding to the backup information, and then encrypt each sensitive data part based on the public key corresponding to the sensitivity to obtain an encrypted data part, and finally transmit the encrypted home data according to the structured label algorithm combination, thereby improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0133] As an optional embodiment, the identification module identifies multiple sensitive data parts and corresponding sensitivity levels in the home data according to the sensitive identification algorithm model corresponding to the device information, including:

[0134] Determine a target sensitive recognition algorithm model from a plurality of preset candidate models according to device information;

[0135] Input each data part of the household data into the target sensitive identification algorithm model to obtain the sensitive type and prediction probability corresponding to each data part;

[0136] According to the sensitivity type and predicted probability, multiple sensitive data parts and corresponding sensitivity levels are screened out from all data parts.

[0137] It can be seen that through the above-mentioned optional embodiments, the target sensitive identification algorithm model can be determined from the preset multiple candidate models based on the device information to predict the sensitivity type and prediction probability corresponding to each data part, and further screen out multiple sensitive data parts and corresponding sensitivity levels, so as to facilitate subsequent data encryption and combination, and assist in improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0138] As an optional embodiment, the specific manner in which the recognition module determines the target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information includes:

[0139] For each candidate model, obtain a set of all prediction sensitive types in the historical prediction results corresponding to the candidate model to obtain prediction result data;

[0140] Determine the possible sensitive type corresponding to the device information according to the preset correspondence between the device information and the sensitive type;

[0141] Calculate the type similarity between the possible sensitive type and the predicted result data to obtain the similarity parameter of the candidate model;

[0142] The candidate model with the highest similarity parameter is determined as the target sensitive recognition algorithm model; the target sensitive recognition algorithm model is trained by a training data set including multiple training home data and corresponding sensitive type annotations of different data parts.

[0143] It can be seen that through the above-mentioned optional embodiments, it is possible to screen a suitable prediction model based on the similarity between the prediction type in the historical prediction results of the candidate model and the possible type corresponding to the device information, so as to facilitate the subsequent prediction of sensitive types, and subsequently realize data encryption and combination, so as to assist in improving the pertinence and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

[0144] As an optional embodiment, the specific manner in which the identification module selects multiple sensitive data parts and corresponding sensitivity levels from all data parts according to the sensitivity type and the predicted probability includes:

[0145] For each data portion, determine the sensitivity score corresponding to the data portion according to the sensitivity type corresponding to the data portion and the preset scoring rule of the sensitivity type;

[0146] Calculate the weighted average of the sensitivity score and the predicted probability to obtain the comprehensive sensitivity probability corresponding to the data portion;

[0147] Determine all data parts whose comprehensive sensitivity probability is higher than a preset probability threshold as sensitive data parts;

[0148] The comprehensive sensitivity probability corresponding to each sensitive data part is determined as its corresponding sensitivity level.

[0149] It can be seen that through the above-mentioned optional embodiments, the sensitivity probability of the data part can be comprehensively determined based on the score of the sensitive type and the prediction probability of the model, so as to screen and determine the sensitivity of specific data parts with high sensitivity and high prediction probability, which is convenient for subsequent data encryption and combination, and helps to improve the targeting and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

[0150] As an optional embodiment, the encryption module encrypts each sensitive data portion according to the public key corresponding to the sensitivity to obtain the encrypted data portion in a specific manner, including:

[0151] Determine a target key library from a plurality of preset key libraries according to the device information; optionally, the device information includes device information of a sending device and a receiving device; the target key library includes encryption algorithms and key pairs that have been determined by the sending device and the receiving device through communication;

[0152] For each sensitive data portion, determining a target algorithm and a target key pair in a target key library according to the sensitivity level corresponding to the sensitive data portion;

[0153] According to the target algorithm and the public key in the target key pair, the sensitive data portion is encrypted to obtain the encrypted data portion.

[0154] It can be seen that through the above-mentioned optional embodiments, the target key library can be determined in the preset multiple key libraries based on the device information, and then the target algorithm and target key pair can be determined in the target key library according to the sensitivity level corresponding to the sensitive data part to realize the encryption of the data part, which is convenient for subsequent data combination and secure transmission, and helps to improve the pertinence and reliability of the home data encryption process, reduce encryption costs, and improve data transmission security.

[0155] As an optional embodiment, the encryption module determines the specific manner of the target algorithm and the target key pair in the target key library according to the sensitivity corresponding to the sensitive data portion, including:

[0156] Determine the encryption algorithm type corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the correspondence between the preset sensitivity level and the encryption algorithm type;

[0157] Determine the key length corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the corresponding relationship between the preset sensitivity level and the key length;

[0158] The target algorithm and the target key pair are determined in the target key library according to the encryption algorithm type and the key length.

[0159] It can be seen that through the above-mentioned optional embodiments, the corresponding encryption algorithm type and key length can be determined based on the corresponding relationship between the preset sensitivity and the algorithm type or key length, and the target algorithm and target key pair can be determined in the target key library to realize encryption of the data part, which is convenient for subsequent data combination and secure transmission, and assists in improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0160] As an optional embodiment, the specific method in which the combination module combines all encrypted data parts and corresponding private key information based on the structured label algorithm to obtain the encrypted home data includes:

[0161] Generate a label structure portion corresponding to each encrypted data portion based on a structured label algorithm;

[0162] For each label structure part, a private key feature identifier corresponding to a private key in a target key pair corresponding to an encrypted data part corresponding to the label structure part is annotated in the label structure part to obtain a corresponding annotated label structure;

[0163] All the annotated label structures and other unencrypted data parts are combined based on a preset combination order to obtain the encrypted home data.

[0164] It can be seen that through the above-mentioned optional embodiments, the label structure part corresponding to each encrypted data part can be generated based on the structured label algorithm, and then marked according to the corresponding private key feature identifier to combine and obtain the encrypted home data, which is convenient for subsequent data security transmission, thereby improving the pertinence and reliability of the home data encryption process, reducing encryption costs, and improving data transmission security.

[0165] As an optional embodiment, the structured tag algorithm is an XML format algorithm, an HTML format algorithm, a YAML format algorithm or a JSON format algorithm.

[0166] It can be seen that through the above optional embodiments, the type of structured labeling algorithm is limited to efficiently implement data structuring and labeling operations, facilitate subsequent data security transmission, improve the pertinence and reliability of home data encryption, reduce encryption costs, and improve data transmission security.

[0167] Embodiment 3

[0168] See also Figure 3 , Figure 3 This is another data security transmission system based on structured tags disclosed in an embodiment of the present invention. Figure 3 The structured tag-based data security transmission system described is applied to a data processing system / data processing device / data processing server (wherein the server includes a local processing server or a cloud processing server). Figure 3 As shown, the data security transmission system based on structured tags may include:

[0169] A memory 301 storing executable program codes;

[0170] a processor 302 coupled to the memory 301;

[0171] The processor 302 calls the executable program code stored in the memory 301 to execute the steps of the data security transmission method based on structured tags described in the first embodiment.

[0172] Embodiment 4

[0173] An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps of the structured tag-based data security transmission method described in the first embodiment.

[0174] Embodiment 5

[0175] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the structured tag-based data security transmission method described in the first embodiment.

[0176] The above describes specific embodiments of the present specification, and other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily have to be performed in the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0177] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0178] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0179] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may be in the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the embodiments of this specification may be in the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0180] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0181] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0182] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0183] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0184] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0185] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0186] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity 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, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0187] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0188] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0189] Finally, it should be noted that the data security transmission method and system based on structured tags disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical scheme of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical schemes described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical schemes from the spirit and scope of the technical schemes of the embodiments of the present invention.

Claims

1. A data security transmission method based on structured tags, characterized in that: The method comprises: Obtaining home data to be transmitted and corresponding device information; Identify multiple sensitive data parts and corresponding sensitivity levels in the home data according to the sensitive identification algorithm model corresponding to the device information; Encrypting each of the sensitive data parts according to the public key corresponding to the sensitivity to obtain an encrypted data part, including: Determine a target key library from a plurality of preset key libraries according to the device information; the device information includes device information of a sending device and a receiving device; the target key library includes a plurality of encryption algorithms and key pairs that have been determined by the sending device and the receiving device through communication; For each of the sensitive data parts, determining a target algorithm and a target key pair in the target key library according to the sensitivity corresponding to the sensitive data part; Encrypting the sensitive data portion according to the target algorithm and the public key in the target key pair to obtain an encrypted data portion; All the encrypted data parts and the corresponding private key information are combined based on the structured label algorithm to obtain encrypted home data for transmission, including: Generate a tag structure portion corresponding to each of the encrypted data portions based on a structured tag algorithm; For each of the label structure parts, a private key feature identifier corresponding to the private key in the target key pair corresponding to the encrypted data part corresponding to the label structure part is marked in the label structure part to obtain a corresponding marked label structure; All the annotated label structures and other unencrypted data parts are combined based on a preset combination order to obtain encrypted home data; after being received, the encrypted home data can be decrypted based on a preset structured recognition rule and a corresponding private key to obtain the home data.

2. The data security transmission method based on structured tags according to claim 1 is characterized in that: The step of identifying multiple sensitive data parts and corresponding sensitivity levels in the home data according to the sensitive identification algorithm model corresponding to the device information includes: Determining a target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information; Input each data portion of the household data into the target sensitivity recognition algorithm model to obtain the sensitivity type and prediction probability corresponding to each data portion; According to the sensitivity type and the predicted probability, a plurality of sensitive data parts and corresponding sensitivity levels are screened out from all the data parts.

3. The data security transmission method based on structured tags according to claim 2 is characterized in that: Determining a target sensitive recognition algorithm model from a plurality of preset candidate models according to the device information includes: For each candidate model, obtain a set of all prediction sensitive types in the historical prediction results corresponding to the candidate model to obtain prediction result data; Determine the possible sensitive type corresponding to the device information according to the preset correspondence between the device information and the sensitive type; Calculating the type similarity between the possible sensitive type and the prediction result data to obtain a similarity parameter of the candidate model; The candidate model with the highest similarity parameter is determined as the target sensitive recognition algorithm model; the target sensitive recognition algorithm model is trained by a training data set including a plurality of training home data and corresponding sensitive type annotations of different data parts.

4. The data security transmission method based on structured tags according to claim 2 is characterized in that: The step of screening out a plurality of sensitive data parts and corresponding sensitivity levels from all the data parts according to the sensitivity type and the predicted probability includes: For each of the data parts, determining a sensitivity score corresponding to the data part according to the sensitivity type corresponding to the data part and a preset scoring rule for the sensitivity type; Calculating a weighted average of the sensitivity score and the predicted probability to obtain a comprehensive sensitivity probability corresponding to the data portion; Determine all the data parts whose comprehensive sensitivity probability is higher than a preset probability threshold as sensitive data parts; The comprehensive sensitivity probability corresponding to each of the sensitive data parts is determined as its corresponding sensitivity level.

5. The data security transmission method based on structured tags according to claim 1 is characterized in that: Determining a target algorithm and a target key pair in the target key library according to the sensitivity corresponding to the sensitive data portion includes: Determine the encryption algorithm type corresponding to the sensitive data portion according to the sensitivity level corresponding to the sensitive data portion and the correspondence between the preset sensitivity level and the encryption algorithm type; Determine the key length corresponding to the sensitive data portion according to the sensitivity corresponding to the sensitive data portion and the corresponding relationship between the preset sensitivity and the key length; A target algorithm and a target key pair are determined in the target key library according to the encryption algorithm type and the key length.

6. The data security transmission method based on structured tags according to claim 1 is characterized in that: The structured tag algorithm is an XML format algorithm, an HTML format algorithm, a YAML format algorithm or a JSON format algorithm.

7. A data security transmission system based on structured tags, characterized in that: The system comprises: An acquisition module, used to acquire home data to be transmitted and corresponding device information; an identification module, configured to identify multiple sensitive data parts and corresponding sensitivity levels in the home data according to a sensitive identification algorithm model corresponding to the device information; An encryption module, used for encrypting each of the sensitive data parts according to the public key corresponding to the sensitivity to obtain an encrypted data part, comprising: Determine a target key library from a plurality of preset key libraries according to the device information; the device information includes device information of a sending device and a receiving device; the target key library includes a plurality of encryption algorithms and key pairs that have been determined by the sending device and the receiving device through communication; For each of the sensitive data parts, determining a target algorithm and a target key pair in the target key library according to the sensitivity corresponding to the sensitive data part; Encrypting the sensitive data portion according to the target algorithm and the public key in the target key pair to obtain an encrypted data portion; A combination module, used for combining all the encrypted data parts and the corresponding private key information based on a structured label algorithm to obtain encrypted home data for transmission, including: Generate a tag structure portion corresponding to each of the encrypted data portions based on a structured tag algorithm; For each of the label structure parts, a private key feature identifier corresponding to the private key in the target key pair corresponding to the encrypted data part corresponding to the label structure part is marked in the label structure part to obtain a corresponding marked label structure; All the annotated label structures and other unencrypted data parts are combined based on a preset combination order to obtain encrypted home data; after being received, the encrypted home data can be decrypted based on a preset structured recognition rule and a corresponding private key to obtain the home data.

8. A data security transmission system based on structured tags, characterized in that: The system comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the data security transmission method based on structured tags as described in any one of claims 1-6.

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