Rare disease data transmission system and method

Abstract

The present application provides a rare disease data transmission system and method, which relates to the field of data encryption technology, wherein the method includes a sending communication node and a receiving communication node determining a modulus value and a primitive value; the sending communication node determining a first random value, and calculating a first exchange value based on the first random value, the modulus value and the primitive value according to a preset algorithm; the receiving communication node determining a second random value, and calculating a second exchange value based on the second random value, the modulus value and the primitive value according to a preset algorithm; the sending communication node and the receiving communication node mutually exchange the first exchange value and the second exchange value; the sending communication node / the receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key. In the case of complex encrypted transmission, the key distribution efficiency can be improved and the encryption computing resources of the medical system can be saved.

Description

Technical Field

[0001] The present application relates to the field of medical data processing technology, and more specifically, to a rare disease data transmission system and method. Background Art

[0002] Medical data related to rare diseases is highly sensitive and, if leaked, could have serious psychological and social impacts on patients. Existing medical systems typically use encryption technology to ensure data security when transmitting sensitive information. The encrypted transmission process of medical data typically involves multiple steps, including key generation, key distribution, data encryption, data transmission, and decryption by the recipient. To ensure security, medical institutions need to regularly update encryption keys and distribute them to authorized users through secure channels. However, these security measures face numerous challenges in implementation. For example, medical data still faces the risk of being cracked during transmission, potentially leaking patients' personal privacy information. Furthermore, existing key management mechanisms, in actual applications, have also exposed complex key distribution processes and the need for frequent updates, which often place an unnecessary burden on the medical system. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide a rare disease data transmission system and method for distributing keys in the encrypted transmission of rare disease medical data, so as to solve the technical problems of complex key distribution process, high update frequency requirement and thus excessive system resource usage.

[0004] In a first aspect, the present invention provides a rare disease data transmission system, comprising a plurality of communication nodes, wherein a symmetric encryption algorithm is used between the communication nodes to transmit rare disease medical data, wherein the communication nodes distribute keys of the symmetric encryption algorithm through the following steps:

[0005] The sending communication node and the receiving communication node determine the modulus value and the primitive value; the sending communication node determines a first random value, and calculates a first exchange value based on the first random value, the modulus value and the primitive value according to a preset algorithm; the receiving communication node determines a second random value, and calculates a second exchange value based on the second random value, the modulus value and the primitive value according to a preset algorithm; the sending communication node and the receiving communication node exchange the first exchange value and the second exchange value with each other; the sending communication node / the receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key.

[0006] In an optional embodiment, when the sending communication node / receiving communication node is a service end and the receiving communication node / sending communication node is a medical end or a patient end, the modulo value and the original value are determined in the following manner:

[0007] The server determines the output modulus value and the original value and sends them to the medical end or the treatment end; when the sending communication node is one of the medical end and the treatment end, and the receiving communication node is the other of the medical end and the treatment end, the output modulus value and the original value are determined in the following way: the server determines the output modulus value and the original value and sends them to the medical end and the treatment end respectively.

[0008] In an optional embodiment, the communication node calculates the exchange value in the following manner:

[0009] The first power value is calculated with the original value as the base and the random value as the exponent; the remainder is calculated as the exchange value with the first power value as the dividend and the modulus value as the divisor.

[0010] In an optional embodiment, the communication node also includes an encryption computing node. Based on the data level of the rare disease medical data, the system adds encryption computing nodes between the transmission links of the rare disease medical data. It also includes: the server determines the modulus value and the original value, and sends them to each encryption computing node.

[0011] In an optional embodiment, the communication node calculates the key by:

[0012] A second power value is calculated based on the received exchange value as the base and the local random value as the exponent; a remainder value is calculated based on the second power value as the dividend and the modulus value as the divisor; and a key is determined based on the remainder value, the exchange value, and the preset relationship table.

[0013] In an optional embodiment, the communication node is specifically used to determine the first English character in a preset relationship table with the remainder value as the horizontal coordinate and the first exchange value as the vertical coordinate; determine the second English character in the preset relationship table with the remainder value as the horizontal coordinate and the second exchange value as the vertical coordinate; generate multiple hexadecimal bytes based on the first exchange value, the second exchange value, the first English character, and the second English character by arranging and combining; and splicing the multiple hexadecimal bytes in a specified order to generate a 128-bit key.

[0014] In an optional embodiment, the server determines the modulus value in the following manner:

[0015] Randomly generate a target value and determine whether the target value is within a preset range; if so, determine the target value as the modulus value; if not, return to the step of randomly generating the target value.

[0016] In an optional implementation, the server determines a primitive value greater than the modulus value based on the determined modulus value.

[0017] In an optional embodiment, the communication node and the encryption computing node set the life cycle of the key based on the data level of the rare disease medical data.

[0018] In a second aspect, the present invention provides a method for transmitting rare disease data, wherein communication nodes distribute keys of a symmetric encryption algorithm through the following steps to encrypt and transmit rare disease medical data using the symmetric encryption algorithm:

[0019] The sending communication node and the receiving communication node determine the modulo value and the original value;

[0020] The sending communication node determines a first random value, and calculates a first exchange value according to a preset algorithm based on the first random value, the modulus value, and the primitive value;

[0021] The receiving communication node determines a second random value, and calculates a second exchange value according to a preset algorithm based on the second random value, the modulus value, and the primitive value;

[0022] The sending communication node and the receiving communication node mutually exchange the first exchange value and the second exchange value;

[0023] The sending communication node / receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key.

[0024] The present application provides a rare disease data transmission system and method, wherein the system includes multiple communication nodes, and a symmetric encryption algorithm is used between the communication nodes to transmit rare disease medical data. The communication nodes distribute the key of the symmetric encryption algorithm through the following steps: the sending communication node and the receiving communication node determine the modulus value and the original value; the sending communication node determines a first random value, and calculates a first exchange value according to a preset algorithm based on the first random value, the modulus value and the original value; the receiving communication node determines a second random value, and calculates a second exchange value according to a preset algorithm based on the second random value, the modulus value and the original value; the sending communication node and the receiving communication node exchange the first exchange value and the second exchange value; the sending communication node / the receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using the symmetric encryption algorithm based on the key. This application generates and distributes keys for each communication node in the rare disease data transmission system based on the DH algorithm. It not only ensures data encryption performance, but also simplifies the key generation process. Even in complex situations with high-frequency key updates and multiple encrypted transmission channels, it can be completed with high efficiency and low computing resource occupancy. The key distribution process can be completely in plain text without the need for additional encryption. Compared with the existing method that requires encrypted transmission of keys, this application can improve key distribution efficiency and save encryption computing resources of the medical system in dealing with complex encrypted transmission situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A schematic diagram of the structure of a rare disease data transmission system provided in an embodiment of the present application;

[0027] Figure 2 A flowchart of a key distribution method provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram of a preset relationship table provided in an embodiment of the present application;

[0029] Figure 4 A flowchart of the steps of a model training method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] First, the application scenarios of this application are described. The technical solution of this application can be applied to data encryption transmission in medical systems, specifically involving key distribution using a symmetric encryption algorithm.

[0031] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0032] Example 1

[0033] Figure 1 The present invention provides a rare disease data transmission system. The system includes multiple communication nodes, which use a symmetric encryption algorithm to transmit rare disease medical data between the communication nodes. The communication nodes may include a medical terminal, a patient terminal, a service terminal, and several encryption computing nodes.

[0034] The medical end can be electronic devices located in different departments and doctors' offices within a medical institution. The patient end can be located on the patient's electronic device. The server and encryption computing nodes can be deployed within the medical institution or in other processing centers located far away from the medical institution.

[0035] The rare disease medical data here can be in different forms of data such as text, pictures, tables, etc., such as case forms, CT images, diagnosis and treatment conversations, etc.

[0036] The transmission channels of the rare disease data transmission system here may include the following methods:

[0037] The sending communication node uses a symmetric encryption algorithm to encrypt and send rare disease medical data directly to the receiving communication node.

[0038] The sending communication node encrypts the data using a symmetric encryption algorithm and sends it to the encryption computing node. After passing through an encryption link formed by at least one encryption computing node, the last encryption computing node sends the encrypted rare disease medical data to the receiving communication node.

[0039] The sending communication node / receiving communication node here can be any one of the medical end, the treatment end, and the service end.

[0040] In this embodiment, encryption computing nodes can be added between transmission links of rare disease medical data based on the data level of the rare disease medical data, and the corresponding key lifecycle can be adjusted. The data level here includes three levels: regular data, private data, and critical data.

[0041] In one possible implementation, for regular data, an encryption computing node may be added or no encryption computing node may be added, and the life cycle of the key may be 24 hours.

[0042] For private data, multiple encryption computing nodes can be added and a dual-node rotation encryption method can be used. The key lifecycle here can be 1 hour. The dual-node rotation here assigns keys to all encryption computing nodes simultaneously. However, the sending communication node randomly selects an encryption computing node from these encryption computing nodes. This encryption computing node then randomly selects another encryption computing node to form an encrypted link. Finally, the other encryption computing node sends the encrypted data to the receiving communication node.

[0043] For critical data, multiple encryption computing nodes can be added, and a three-node chain encryption method can be used. Here, the key lifecycle can be single-use. This three-node chain encryption method is similar to the principle of selecting encryption computing nodes in a two-node rotation, except that three encryption computing nodes are used in the encryption chain.

[0044] Furthermore, a key replacement mechanism can be triggered based on medical operation events, such as automatically updating the key when a patient transfers to another department; a modification of a medical order triggers the rotation of related data keys; an abnormal access attempt triggers an emergency key reset, etc.

[0045] The present application provides a rare disease data transmission system, which can improve the security of rare disease medical data transmission through dynamic key derivation combined with a hierarchical encryption method of multi-node links.

[0046] Example 2

[0047] In one embodiment of the present application, based on the rare disease data transmission system provided in the above embodiment, a key distribution method based on the DH algorithm is proposed due to the complex scenarios in which the system has high key update frequency, frequent communications between communication nodes, and a large number of key requirements.

[0048] like Figure 2 Specifically, the communication nodes can distribute the key of the symmetric encryption algorithm through the following steps:

[0049] S1. The sending communication node and the receiving communication node determine the modulus value and the original value.

[0050] The modulus value and original value here can be determined by the server and then sent to the corresponding communication node.

[0051] Exemplarily, when the sending communication node / receiving communication node is a server, and the receiving communication node / sending communication node is a medical terminal or a clinic terminal, the server determines the modulus value and the original value and sends them to the medical terminal or the clinic terminal.

[0052] When the sending communication node is one of the medical end and the treatment end, and the receiving communication node is the other of the medical end and the treatment end, the server determines the module value and the original value and sends them to the medical end and the treatment end respectively.

[0053] Furthermore, the modulus and primitive values ​​of each encryption computing node can also be sent by the server. That is, when adding encryption computing nodes between the transmission links of rare disease medical data, the server determines the modulus and primitive values ​​and sends them to each encryption computing node.

[0054] It should be noted that any two adjacent nodes in an encrypted link need to be assigned the same modulus value and primitive value.

[0055] S2. The sending communication node determines a first random value, and calculates a first exchange value according to a preset algorithm based on the first random value, the modulus value, and the primitive value.

[0056] S3. The receiving communication node determines a second random value, and calculates a second exchange value according to a preset algorithm based on the second random value, the modulus value, and the primitive value.

[0057] In steps S2 and S3, the communication node can randomly determine the first random value and the second random value. The size of the random value is not limited. The exchange value can be calculated using a modular operation.

[0058] Specifically, the communication nodes can calculate the exchange value in the following way:

[0059] The first power value is calculated with the original value as the base and the random value as the exponent; the remainder is calculated as the exchange value with the first power value as the dividend and the modulus value as the divisor.

[0060] The specific calculation formula of the exchange value can be expressed as:

[0061] ;

[0062] ;

[0063] in, is the first exchange value, is the second exchange value, is the first random value, is the second random value, is the original value, is the modulus value.

[0064] S4. The sending communication node and the receiving communication node exchange the first exchange value and the second exchange value.

[0065] Here, the sending communication node calculates its own Send to the receiving communication node. The receiving communication node calculates Sent to the sending communication node.

[0066] Moreover, the exchange value can be exchanged in plain text here.

[0067] S5. The sending communication node / receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key.

[0068] In step S5, the communication node can calculate the key by:

[0069] The second power value is calculated based on the received exchange value as the base and the local random value as the exponent. The remainder value is calculated based on the second power value as the dividend and the modulus value as the divisor.

[0070] The calculation formula of the remainder value can be expressed as:

[0071] ;

[0072] ;

[0073] in, The first remainder value calculated by the sending communication node, The second remainder value calculated by the receiving communication node, is the first exchange value, is the second exchange value, is the first random value, is the second random value, is the original value, is the modulus value.

[0074] It should be noted that if the correct exchange step of the exchange value is completed between the sending communication node and the receiving communication node, the first remainder value and the second remainder value here are the same.

[0075] Furthermore, a step of verifying the remainder value calculated between the sending communication node and the receiving communication node may be added to the key distribution step. If the verification is correct, the key generation step is performed.

[0076] Finally, the key can be determined based on the remainder value, the exchange value, and the preset relationship table, where the preset relationship table is used to indicate the mapping relationship between numbers and English characters.

[0077] Specifically, the first English character is determined in the preset relationship table using the remainder value as the horizontal coordinate and the first exchange value as the vertical coordinate. The second English character is determined in the preset relationship table using the remainder value as the horizontal coordinate and the second exchange value as the vertical coordinate.

[0078] Here, the determination of the abscissa and the ordinate may also be other selection methods between the remainder value, the first exchange value, and the second exchange value, which is not limited.

[0079] Based on the first exchange value, the second exchange value, the first English character, and the second English character, multiple hexadecimal bytes are generated. The multiple hexadecimal bytes are concatenated in a specified order to generate a 128-bit key.

[0080] In this way, the keys generated between the sending communication node and the receiving communication node are the same, and the encryption or decryption process of the rare disease medical data can be correctly completed.

[0081] The present application provides a rare disease data transmission system, which generates and distributes keys for each communication node in the rare disease data transmission system based on the DH algorithm. The key generation process adopts simple modular operation, which is fast to calculate, and the key generation process does not require encrypted communication. Even in the case of complex encrypted transmission, the key distribution efficiency is still high and the encryption computing resources of the medical system are less occupied.

[0082] Example 3

[0083] In one embodiment of the present application, the efficiency of key distribution can be adjusted based on different response rate requirements.

[0084] Specifically, the key generation rate can be adjusted by limiting the size of the modulus value.

[0085] In one embodiment, the server can determine the modulus value in the following manner:

[0086] Randomly generate a target value and determine whether the target value is within a preset range. If so, determine the target value as the modulus value. If not, return to the step of randomly generating the target value.

[0087] The server determines an original value greater than the modulus value based on the determined modulus value.

[0088] In one embodiment, the modulus value The range of the value of is [1,10]. This ensures that the calculated remainder value is in the range of [0,9]. The value range of is [1,10]. The following example illustrates the key generation process:

[0089] In step S5, It can be 3, The first remainder value can be determined by sending the communication node for 2 =1, first exchange value =2, second exchange value =1.

[0090] The preset relationship table can be found in Figure 3 The sending communication node uses the first remainder value as the horizontal coordinate and the first exchange value as the vertical coordinate to determine the first English character A in the preset relationship table. The sending communication node uses the first remainder value as the horizontal coordinate and the second exchange value as the vertical coordinate to determine the second English character D in the preset relationship table.

[0091] The sending communication node generates multiple hexadecimal bytes based on the first exchange value, the second exchange value, the first English character, and the second English character by arrangement and combination, which may specifically include 33, 34, 3A, 3D, 44, 43, 4A, 4D, AA, AD, A3, A4, DD, DA, D3, and D4.

[0092] Concatenating the 16 hexadecimal bytes in the preceding example in the specified order to generate a 128-bit key can be 33343A3D44434A4DAAADA3A4DDDAD3D4.

[0093] The receiving node generates a key similarly to the sending node, except that the receiving node uses the second remainder value as the horizontal coordinate and the first exchange value as the vertical coordinate, and determines from the preset relationship table that the first English character is also A. Using the first remainder value as the horizontal coordinate and the second exchange value as the vertical coordinate, the receiving node determines from the preset relationship table that the second English character is also D.

[0094] That is, in the above embodiment, the key generated by the receiving communication node is also 33343A3D44434A4DAAADA3A4DDDAD3D4.

[0095] It should be noted that the splicing order of bytes may be a fixed splicing order preset in each communication node, or a pre-specified splicing order.

[0096] The embodiment of the present application provides a rare disease data transmission system, which has a simple calculation method for key generation and distribution at each node and high distribution efficiency, and can well cope with encryption scenarios with a large number of keys and high update frequency.

[0097] Example 4

[0098] In one embodiment of the present application, the rare disease medical data transmitted between communication nodes can also be data generated during the training of the disease analysis model. The server can provide services to different medical institutions. The communication nodes here can be medical terminals deployed in different medical institutions.

[0099] like Figure 4 As shown, the model training can be completed between the server and the medical end through the following steps:

[0100] Step 1: The server generates global model parameters and initial analysis model based on the medical data analysis request initiated by the target medical terminal, and sends them to multiple medical terminals.

[0101] The target medical end here is the target medical institution that initiated the medical data analysis request. After the medical data analysis request is sent to the server, the server will broadcast it to the corresponding medical ends of the remaining medical institutions.

[0102] Among them, the medical data analysis request is used to indicate the types of medical data and rare diseases to be analyzed by the medical institution corresponding to the target medical end, and the multiple medical ends include the target medical end and other medical ends that join the medical data analysis request.

[0103] The remaining medical institutions can independently choose whether to respond to the medical data analysis request and use local medical data to help the target medical institutions jointly train and generate AI models.

[0104] For example, Target Medical Institution A initiates a medical data analysis request, specifying that the medical data to be analyzed is medical imaging, specifically coronary CTA images, and that the rare disease to be analyzed is coronary artery ectasia. This means that the AI ​​model Target Medical Institution A intends to build can take a patient's coronary CTA image as input, and output analysis results such as disease probability, disease severity, or identification of key diseased areas.

[0105] The remaining medical institutions can choose whether to join the medical data analysis request of target medical institution A based on the situation of their local medical data.

[0106] Furthermore, the server can determine the target medical institution A and other medical institutions B, C, D, and E that have joined the medical data analysis request and send global model parameters and initial analysis models to the respective medical terminals of medical institutions A, B, C, D, and E.

[0107] The server can match the appropriate AI model and corresponding global model parameters based on the type of medical data and rare diseases being analyzed by the target medical institution indicated in the medical data analysis request. For example, if the medical data is medical imaging, a CNN (Convolutional Neural Network) can be selected as the initial analysis model. If the medical data is time series data such as electrocardiograms, an RNN (Recurrent Neural Network) can be selected as the initial analysis model. The global model parameters here can be commonly used initial values ​​set based on experience.

[0108] Step 2: For each medical end, the initial analysis model is trained based on the local medical data of the medical end to obtain the local analysis model of the medical end, and the local model parameters and loss function values ​​of the local analysis model are sent to the server. The local medical data is matched with the medical data type and rare disease type.

[0109] Each medical terminal at different medical institutions A, B, C, D, and E begins training the initial analysis model using local medical data. The training method, including the loss function and number of iterations, can be uniformly specified by the server, such as 5 or 10 rounds per round, for a total of 10 rounds. For example, medical institution A inputs the initial analysis model using coronary CTA images of patient A and trains it to output the probability that patient A is ill. Medical institution B can then input the initial analysis model using coronary CTA images of patient B and train it to output the probability that patient B is ill. Similarly, each local analysis model is derived.

[0110] After each round of iteration, each medical end can feed back the local model parameters and loss function value of the current local analysis model to the server, which can be specifically expressed as 、 、……、 ,in, 、 、 、 They are different sub-parameter items of the local analysis model. Lost is the loss function value.

[0111] Step 3: The server inputs the multiple local model parameters and loss function values ​​received in this round into the particle swarm optimization model to obtain the optimized model parameters output by the particle swarm optimization model, and sends the optimized model parameters to each medical end to update the model parameters of the initial analysis model in the medical end.

[0112] The server receives - Input to the particle swarm optimization model, such as Figure 2 As shown, the particle swarm optimization model can output the optimization model parameters for each round in the following ways:

[0113] S100. The local model parameters sent by each medical terminal in this round are used as the position of particle i, and the loss function difference of each medical terminal is used as the speed of the corresponding particle i.

[0114] Among them, the loss function difference is the difference between the loss function value sent by the medical end in this round and the average of the loss function value in the previous round.

[0115] For each particle i, its position can be expressed as , 、……、 .

[0116] For each particle i, its velocity can be expressed as = - , = - 、……、 = - .in, It is the mean of the loss function values ​​corresponding to all medical terminals in the previous round.

[0117] S101: Determine whether a convergence condition is met.

[0118] The convergence condition here can be the number of iterations, etc.

[0119] And the fitness value of each particle is calculated through the objective function and compared with the optimal position of the particle to update the optimal position of the particle.

[0120] S102: If not, update the position and velocity of each particle i, and return to the step of determining whether the convergence condition is met.

[0121] In step S102, the position and velocity of each particle i can be updated in the following way:

[0122] + + ( );

[0123] + ;

[0124] in, is the updated velocity of particle i, is the velocity of particle i before updating, is the updated position of particle i, is the position of particle i before updating, is the optimal position of particle i, is the global optimal position, 、 To learn the parameter value (usually = =2), 、 is a random parameter value, taking the value [0,1], i=1, 2, 3...N, N is the total number of particles.

[0125] S103: If yes, output the optimal particle position and the global optimal position of each particle i as optimization model parameters.

[0126] Finally, when the convergence condition is met, the optimal particle position and the global optimal position of each particle i can be obtained.

[0127] Step 4: The server determines an optimized analysis model based on the optimized model parameters and determines whether the optimized analysis model meets the preset conditions. If not, the server returns to step 2. If yes, the server sends the optimized analysis model to the target medical terminal.

[0128] The server can use the optimized model parameters as the model parameters of the initial analysis model to determine the optimized analysis model. It can then calculate the accuracy of the optimized analysis model. When the accuracy meets the requirements, the iteration can be ended and the optimized analysis model is sent to the target medical end. If the accuracy does not meet the requirements, the optimized model parameters are fed back to each medical end, allowing the medical end to continue iterative training.

[0129] Step 5: The target medical end inputs the medical data to be tested that matches the medical data type into the optimization analysis model to obtain the analysis results corresponding to the rare disease types output by the optimization analysis model.

[0130] The target medical end can obtain corresponding analysis results through the final optimized analysis model. The optimized analysis model here has higher accuracy and better generalization ability, which in turn provides better auxiliary effects in the analysis of rare diseases.

[0131] For the communication process between steps one to five, the SM2CBC algorithm can be used for encryption, and the key used in the encryption process can be generated by the method provided by the aforementioned implementation.

[0132] In an embodiment of the present application, data encryption is performed during the training process of the rare disease analysis model to further protect the security of rare disease data.

[0133] Example 5

[0134] In an embodiment of the present application, a method for transmitting rare disease data is provided. The communication nodes distribute keys of a symmetric encryption algorithm through the following steps to encrypt and transmit rare disease medical data using a symmetric encryption algorithm:

[0135] The sending communication node and the receiving communication node determine the modulo value and the original value;

[0136] The sending communication node determines a first random value, and calculates a first exchange value according to a preset algorithm based on the first random value, the modulus value, and the primitive value;

[0137] The receiving communication node determines a second random value, and calculates a second exchange value according to a preset algorithm based on the second random value, the modulus value, and the primitive value;

[0138] The sending communication node and the receiving communication node mutually exchange the first exchange value and the second exchange value;

[0139] The sending communication node / receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key.

[0140] The embodiment of the present application provides a rare disease data transmission method, which has the same technical effect as the rare disease data transmission system and will not be described in detail here.

[0141] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0142] In addition, the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0143] Furthermore, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0144] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the existing technology, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program code.

[0145] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0146] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A rare disease data transmission system, characterized in that: The system includes multiple communication nodes, including medical terminals, consultation terminals, service terminals and encryption computing nodes. A symmetric encryption algorithm is used between the communication nodes to transmit rare disease medical data. Based on the data level of the rare disease medical data, encryption computing nodes are added between the transmission links of the rare disease medical data, and the service terminal determines the modulus value and the original value and sends them to each encryption computing node. Among them, the key distribution of the symmetric encryption algorithm is carried out between two adjacent communication nodes in the transmission link of rare disease medical data through the following steps: The sending communication node and the receiving communication node obtain the modulus value and the primitive value determined by the server; The sending communication node determines a first random value, and calculates a first exchange value according to a preset algorithm based on the first random value, the modulus value, and the primitive value; The receiving communication node determines a second random value, and calculates a second exchange value according to a preset algorithm based on the second random value, the modulus value, and the primitive value; The sending communication node and the receiving communication node mutually exchange the first exchange value and the second exchange value; The sending communication node / receiving communication node calculates a key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key; The communication node calculates the key in the following way: Calculate a second power value based on the received exchange value as the base and the local random value as the exponent; Use the second power value as the dividend and the modulus value as the divisor to calculate the remainder value; Using the remainder value as the horizontal coordinate and the first exchange value as the vertical coordinate, determine the first English character in the preset relationship table; Using the remainder value as the horizontal coordinate and the second exchange value as the vertical coordinate, determine the second English character in the preset relationship table; Generate multiple hexadecimal bytes by performing permutations and combinations based on the first exchange value, the second exchange value, the first English character, and the second English character; Concatenates multiple hexadecimal bytes in a specified order to generate a 128-bit key.

2. The system according to claim 1, wherein: When the sending communication node / receiving communication node is the server, and the receiving communication node / sending communication node is either the medical terminal or the patient terminal, the output modulus value and the original value are determined in the following way: The server determines the modulus value and original value and sends them to the medical terminal or the consultation terminal; When the sending communication node is one of the medical end and the patient end, and the receiving communication node is the other of the medical end and the patient end, the modulo value and the original value are determined in the following way: The server determines the output value and original value and sends them to the medical end and the consultation end respectively.

3. The system according to claim 1, wherein: The communicating nodes calculate the exchange value in the following way: Calculate the first power value with the original value as the base and the random value as the exponent; Use the first power value as the dividend and the modulus value as the divisor, and calculate the remainder as the exchange value.

4. The system according to claim 1, wherein: The server determines the modulus value in the following way: Randomly generate a target value and determine whether the target value is within a preset range; If so, the target value is determined as the modulus value; If not, return to the step of randomly generating the target value.

5. The system according to claim 4, characterized in that The server determines a primitive value greater than the modulus value based on the determined modulus value.

6. The system according to claim 1, wherein: Communication nodes and encryption computing nodes set the key life cycle based on the data level of rare disease medical data.

7. A method for transmitting rare disease data, characterized in that: The communication nodes include the medical end, the treatment end, the server end, and the encryption computing node. Based on the data level of the rare disease medical data, the encryption computing node is added between the transmission links of the rare disease medical data, and the server end determines the modulus value and the original value and sends them to each encryption computing node. The key of the symmetric encryption algorithm is distributed between two adjacent communication nodes in the transmission link of the rare disease medical data through the following steps to use the symmetric encryption algorithm for encrypted transmission of the rare disease medical data: The sending communication node and the receiving communication node obtain the modulus value and the primitive value determined by the server; The sending communication node determines a first random value, and calculates a first exchange value according to a preset algorithm based on the first random value, the modulus value, and the primitive value; The receiving communication node determines a second random value, and calculates a second exchange value according to a preset algorithm based on the second random value, the modulus value, and the primitive value; The sending communication node and the receiving communication node mutually exchange the first exchange value and the second exchange value; The sending communication node / the receiving communication node calculates a key based on the first exchange value and the second exchange value, and encrypts and transmits the rare disease medical data using a symmetric encryption algorithm based on the key; The communication node calculates the key in the following way: Calculate a second power value based on the received exchange value as the base and the local random value as the exponent; Use the second power value as the dividend and the modulus value as the divisor to calculate the remainder value; Determine a key based on the remainder value, the exchange value, and the preset relationship table; Using the remainder value as the horizontal coordinate and the first exchange value as the vertical coordinate, determine the first English character in the preset relationship table; Using the remainder value as the horizontal coordinate and the second exchange value as the vertical coordinate, determine the second English character in the preset relationship table; Generate multiple hexadecimal bytes by performing permutations and combinations based on the first exchange value, the second exchange value, the first English character, and the second English character; Concatenates multiple hexadecimal bytes in a specified order to generate a 128-bit key.

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