Rare disease data transmission system and method

Abstract

The invention provides a rare disease data transmission system and method, and relates to the technical field of data encryption, and the method comprises the steps: a transmitting communication node and a receiving communication node determine a module value and an 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 module value and the original value; receiving a second random value determined by the communication node, and calculating a second exchange value according to a preset algorithm based on the second random value, the module value and the original value; 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 / receiving communication node calculates the secret key based on the received exchange value and the local random value, and encrypts and transmits the rare disease medical data by adopting the symmetric encryption algorithm based on the secret key, so that the secret key distribution efficiency can be improved and the encryption calculation resources of the medical system can be saved under the condition of coping with complex encryption transmission.

Description

Technical Field

[0001] This application relates to the technical field of medical data processing. Specifically, it relates to a rare disease data transmission system and method. Background Art

[0002] Rare disease medical data is highly sensitive, and once leaked, it may cause serious psychological and social impacts on patients. When existing medical systems transmit sensitive information, they usually use encryption technology to ensure data security. The encrypted transmission process of medical data usually involves multiple links such as key generation, key distribution, data encryption, data transmission, and decryption by the receiving party. To ensure security, medical institutions need to regularly update encryption keys and distribute the keys to authorized users through secure channels. However, these security measures face many challenges in the implementation process. For example, there is still a risk that medical data may be cracked during transmission, which may leak patients' personal privacy information. At the same time, the existing key management mechanism also exposes problems such as complex key distribution processes and high-frequency updates in practical applications, which often impose unnecessary burdens on medical systems. Summary of the Invention

[0003] The purpose of the embodiments of this application is to provide a rare disease data transmission system and method, aiming at the key distribution in the encrypted transmission of rare disease medical data, and solving the technical problems of complex key distribution processes, high update frequency requirements, and thus excessive system resource occupancy.

[0004] In a first aspect, the present invention provides a rare disease data transmission system. The system includes multiple communication nodes, and symmetric encryption algorithms are used for the transmission of rare disease medical data between the communication nodes. Among them, the communication nodes perform key distribution of the symmetric encryption algorithm through the following steps: 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 / receiving communication node calculates the 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.

[0005] In an optional embodiment, when the sending communication node / receiving communication node is the server, and the receiving communication node / sending communication node is one of the medical end or the visiting end, the modulus value and the primitive value are determined in the following manner: The server determines the modulus value and the original value, and sends them to the medical end or the consultation end; when the sending communication node is one of the medical end and the consultation end, and the receiving communication node is the other of the medical end and the consultation end, the modulus value and the original value are determined in the following way: The server determines the modulus value and the original value, and sends them to the medical end and the consultation end respectively.

[0006] In an alternative embodiment, the communication node calculates the exchange value in the following way: Taking the original value as the base and the random value as the exponent, calculate the first power value; taking the first power value as the dividend and the modulus value as the divisor, calculate the remainder as the exchange value.

[0007] In an alternative embodiment, the communication node further includes an encryption calculation node. The system adds encryption calculation nodes between the transmission links of the rare disease medical data based on the data level of the rare disease medical data, and further includes: The server determines the modulus value and the original value, and sends them to each encryption calculation node.

[0008] In an alternative embodiment, the communication node calculates the key in the following way: Based on the received exchange value as the base and the local random value as the exponent, calculate the second power value; taking the second power value as the dividend and the modulus value as the divisor, calculate the remainder value; based on the remainder value, the exchange value and the preset relationship table, determine the key.

[0009] In an alternative embodiment, the communication node is specifically used to determine the first English character in the preset relationship table with the remainder value as the abscissa and the first exchange value as the ordinate; determine the second English character in the preset relationship table with the remainder value as the abscissa and the second exchange value as the ordinate; generate multiple hexadecimal bytes based on the first exchange value, the second exchange value, the first English character, and the second English character; splice the multiple hexadecimal bytes in a specified order to generate a 128-bit key.

[0010] In an alternative embodiment, the server determines the modulus value in the following way: Randomly generate a target value, and determine whether the target value is within the preset range; if so, determine the target value as the modulus value; if not, return to execute the step of randomly generating the target value.

[0011] In an alternative embodiment, the server determines the original value greater than the modulus value based on the determined modulus value.

[0012] In an alternative embodiment, the communication node and the encryption calculation node set the lifecycle of the key based on the data level of the rare disease medical data. Second aspect, the present invention provides a method for transmitting rare disease data. The key distribution of the symmetric encryption algorithm between communication nodes is carried out through the following steps to encrypt and transmit rare disease medical data by using the symmetric encryption algorithm: The sending communication node and the receiving communication node determine the modulus value and the original value of the local node. 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 original 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 original 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 / 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 by using the symmetric encryption algorithm based on the key.

[0013] A rare disease data transmission system and method provided by the present application. The system includes multiple communication nodes. The communication nodes use the symmetric encryption algorithm to transmit rare disease medical data. The key distribution of the symmetric encryption algorithm between the communication nodes is carried out through the following steps: The sending communication node and the receiving communication node determine the modulus value and the original value of the local node. 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 original 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 original 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 / 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 by using the symmetric encryption algorithm based on the key. The present application generates and distributes keys for each communication node in the rare disease data transmission system based on the DH algorithm, which can not only ensure the data encryption performance, but also has a simple key generation process. Even in the complex situations of high-frequency key update and multiple encryption transmission channels, it can be completed with high efficiency and low computing resource occupation. And the key distribution process can be completely carried out in plain text without additional encryption. Compared with the prior art that requires encrypting and transmitting keys, the present application can improve the key distribution efficiency and save the encryption computing resources of the medical system in dealing with complex encryption transmission situations. Brief Description of the Drawings

[0014] To more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as a limitation of the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0015] Figure 1 It is a schematic structural diagram of a rare disease data transmission system provided by an embodiment of the present application; Figure 2 It is a step flowchart of a key distribution method provided by an embodiment of the present application; Figure 3 It is a schematic diagram of a preset relationship table provided by an embodiment of the present application; Figure 4 It is a step flowchart of a model training method provided by an embodiment of the present application. Detailed implementation manners

[0016] First, the applicable scenarios of the present application are described. The technical solutions of the present application can be applied to the encrypted transmission of data in a medical system, specifically involving the key distribution using a symmetric encryption algorithm.

[0017] Next, the technical solutions in the embodiments of the present application will be described in conjunction with the drawings in the embodiments of the present application.

[0018] Embodiment 1 Figure 1 It is a rare disease data transmission system provided by an embodiment of the present application. The system includes multiple communication nodes, and symmetric encryption algorithms are used for the transmission of rare disease medical data between the communication nodes. Here, the communication nodes can include a medical end, a patient visit end, a server end, and several encryption calculation nodes.

[0019] Here, the medical end can be electronic devices on the sides of different doctors in different departments of a medical institution. The patient visit end can be set on the patient's electronic device. The server end and the encryption calculation nodes can be deployed within a medical institution or in other processing centers far from the medical institution.

[0020] Here, the rare disease medical data can be data in different forms such as text, pictures, tables, etc., such as case tables, CT pictures, diagnosis and treatment conversations, etc.

[0021] The transmission channels of the rare disease data transmission system here can include the following several methods: The sending communication node directly sends the rare disease medical data to the receiving communication node after encrypting it using a symmetric encryption algorithm.

[0022] The sending communication node encrypts the data using a symmetric encryption algorithm and then sends it to the encryption calculation node. After passing through an encryption link composed of at least one encryption calculation node, the last encryption calculation node sends the encrypted rare disease medical data to the receiving communication node.

[0023] The sending communication node / receiving communication node here can be any one of the medical end, the medical treatment end, and the service end.

[0024] In this embodiment, encryption calculation nodes can be added between the transmission links of the rare disease medical data based on the data level of the rare disease medical data, and the corresponding key lifecycle can be adjusted. Here, the data level includes three levels: classified as regular data, privacy data, and critical data.

[0025] In an implementable manner, for regular data, one encryption calculation node can be added or no encryption calculation node can be added. Here, the lifecycle of the key can be 24 hours.

[0026] For privacy data, multiple encryption calculation nodes can be added, and a dual-node rotation encryption method can be used. Here, the lifecycle of the key can be 1 hour. The dual-node rotation here means that keys are assigned to all encryption calculation nodes simultaneously, but the sending communication node randomly selects one encryption calculation node from these encryption calculation nodes, and this encryption calculation node then randomly selects another encryption calculation node to form an encryption link. Finally, the other encryption calculation node sends the encrypted data to the receiving communication node.

[0027] For critical data, multiple encryption calculation nodes can be added, and a three-node chain encryption method can be used. Here, the lifecycle of the key can be valid only once. The three-node chain encryption here can be similar to the principle of selecting encryption calculation nodes in the dual-node rotation, the difference being that three encryption calculation nodes are used in the formed encryption link.

[0028] Furthermore, a key replacement mechanism can also be based on the trigger of medical operation events, such as automatically updating the key when a patient is transferred to another department; the modification of medical orders triggers the rotation of relevant data keys; an abnormal access attempt causes an emergency key reset, etc.

[0029] A rare disease data transmission system provided by this application can improve the security of rare disease medical data transmission through dynamic key derivation and combined with a hierarchical encryption method for multi-node links.

[0030] Embodiment 2 In an embodiment of this application, based on the rare disease data transmission system provided in the above embodiment, due to the complex scenarios of high key update frequency, frequent communication between communication nodes, and a large number of key requirements in the system, a key distribution method based on the DH algorithm is proposed.

[0031] As Figure 2 described above, specifically, the key distribution of the symmetric encryption algorithm between communication nodes can be carried out through the following steps: S1. The sending communication node and the receiving communication node determine the modulus value and the base value.

[0032] Here, the modulus value and the base value can be determined by the server side and then sent to the corresponding communication nodes.

[0033] Exemplarily, when the sending communication node / receiving communication node is the server side and the receiving communication node / sending communication node is one of the medical side or the visiting side, the server side determines the modulus value and the base value and sends them to the medical side or the visiting side.

[0034] When the sending communication node is one of the medical side and the visiting side, and the receiving communication node is the other of the medical side and the visiting side, the server side determines the modulus value and the base value and sends them to the medical side and the visiting side respectively.

[0035] In addition, the modulus value and the base value of each encryption calculation node can also be sent by the server side. That is, when adding encryption calculation nodes between the transmission links of rare disease medical data, the server side determines the modulus value and the base value and sends them to each encryption calculation node.

[0036] It should be noted that for any two adjacent nodes in the encryption link, the same modulus value and base value need to be allocated.

[0037] S2. The sending communication node determines the first random value and calculates the first exchange value based on the first random value, the modulus value and the base value according to a preset algorithm.

[0038] S3. The receiving communication node determines the second random value and calculates the second exchange value based on the second random value, the modulus value and the base value according to a preset algorithm.

[0039] In steps S2 and S3, the communication node can randomly determine the first random value and the second random value by itself. The size of the random value here is not limited. The calculation method of the exchange value here can adopt the modulo operation method.

[0040] Specifically, the communication node can calculate the exchange value through the following method: Taking the base value as the base and the random value as the exponent, calculate the first power value; taking the first power value as the dividend and the modulus value as the divisor, calculate the remainder as the exchange value.

[0041] The specific calculation formula of the exchange value can be expressed as: ; ; Wherein, 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.

[0042] S4. The sending communication node and the receiving communication node exchange the first exchange value and the second exchange value with each other.

[0043] Here, the sending communication node sends the calculated by itself to the receiving communication node. The receiving communication node sends the calculated by itself to the sending communication node.

[0044] And, here, the exchange of the exchange values can be performed in plain text.

[0045] 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 this key.

[0046] In step S5, the communication node can calculate the key in the following way: Based on the received exchange value as the base and the local random value as the exponent, calculate the second power value. Using the second power value as the dividend and the modulus value as the divisor, calculate the remainder value.

[0047] The calculation formula of the remainder value can be expressed as: ; ; where, is the first remainder value calculated by the sending communication node, is 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.

[0048] It should be noted that if the correct exchange value exchange steps are completed between the sending communication node and the receiving communication node, the first remainder value and the second remainder value here are the same.

[0049] Furthermore, a step of verifying the calculated remainder values between the sending communication node and the receiving communication node can also be added in the key distribution step. If the verification is correct, then the step of generating the key is executed.

[0050] Finally, a secret key can be determined based on the remainder value, the exchange value, and a preset relationship table. Here, the preset relationship table is used to indicate the mapping relationship between numbers and English characters.

[0051] Specifically, with the remainder value as the abscissa and the first exchange value as the ordinate, the first English character is determined in the preset relationship table. With the remainder value as the abscissa and the second exchange value as the ordinate, the second English character is determined in the preset relationship table.

[0052] Here, the determination of the abscissa and ordinate can also be other selection methods among the remainder value, the first exchange value, and the second exchange value, which is not limited.

[0053] Based on the first exchange value, the second exchange value, the first English character, and the second English character, permutations and combinations are performed to generate multiple hexadecimal bytes. The multiple hexadecimal bytes are concatenated in a specified order to generate a 128-bit secret key.

[0054] In this way, the secret keys generated between the sending communication node and the receiving communication node are the same, and the encryption or decryption process of rare disease medical data can be correctly completed.

[0055] A rare disease data transmission system provided by the present application generates and distributes secret keys for each communication node in the rare disease data transmission system based on the DH algorithm. The secret key generation process uses simple modulo operations, with fast calculations. And the secret key generation process does not require encrypted communication. Even in the face of complex encrypted transmission situations, the secret key distribution efficiency is still high, and the encryption computing resources of the medical system are less occupied.

[0056] Embodiment III In an embodiment of the present application, the efficiency of secret key distribution can be adjusted based on different response rate requirements.

[0057] Specifically, the secret key generation rate can be adjusted by limiting the size of the modulus value.

[0058] In one implementation manner, the server can determine 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 execute the step of randomly generating the target value.

[0059] Based on the determined modulus value, the server determines a primitive value greater than the modulus value.

[0060] In a specific embodiment, the modulus value has a value range of [1, 10]. This can ensure that the value range of the calculated remainder value is [0, 9]. The following takes The value range of is [1,10]. The following example illustrates the key generation process: 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.

[0061] 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.

[0062] 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.

[0063] Concatenating the 16 hexadecimal bytes in the preceding example in the specified order to generate a 128-bit key can be 33343A3D44434A4DAAADA3A4DDDAD3D4.

[0064] 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.

[0065] That is, in the above embodiment, the key generated by the receiving communication node is also 33343A3D44434A4DAAADA3A4DDDAD3D4.

[0066] 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.

[0067] 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.

[0068] Example 4 In an embodiment of the present application, the rare disease medical data transmitted between communication nodes may also be the data generated during the training process of the disease analysis model. The server can provide services to different medical institutions. Here, the communication nodes can be medical terminals deployed in different medical institutions.

[0069] As Figure 4 shown, the following steps can be used to complete model training between the server and the medical terminal: Step 1: The server generates global model parameters and an initial analysis model according to the medical data analysis request initiated by the target medical terminal, and sends them to multiple medical terminals.

[0070] Here, the target medical terminal is the target medical institution that initiates the medical data analysis request. After the medical data analysis request is sent to the server, the server will broadcast it to the medical terminals corresponding to the remaining medical institutions.

[0071] Among them, the medical data analysis request is used to indicate the types of medical data and rare disease types to be analyzed by the medical institution corresponding to the target medical terminal. The multiple medical terminals include the target medical terminal and other medical terminals that join the medical data analysis request.

[0072] The remaining medical institutions can independently choose whether to respond to the medical data analysis request and help the target medical institution jointly train and generate an AI model through local medical data.

[0073] Exemplarily, target medical institution A initiates a medical data analysis request. The medical data analysis request indicates that the type of medical data to be analyzed is medical imaging, specifically coronary CTA images. The medical data analysis request indicates that the rare disease type to be analyzed can be coronary artery dilation disease. That is, the input of the AI model that target medical institution A wants to build can be the coronary CTA images of patients, and the output can be analysis results such as the probability of getting sick, the degree of illness, or the key areas where the illness is identified.

[0074] The remaining medical institutions can choose whether to join the medical data analysis request of target medical institution A according to the situation of local medical data.

[0075] Furthermore, the server can determine target medical institution A and other medical institutions B, C, D, and E that join the medical data analysis request, and send the global model parameters and the initial analysis model to the medical terminals of medical institutions A, B, C, D, and E respectively.

[0076] The server can match a suitable AI model and corresponding global model parameters according to the types of medical data and rare disease types to be analyzed indicated by the medical data analysis request for the target medical institution. For example, when the type of medical data is medical imaging, CNN (Convolutional Neural Networks) can be selected as the initial analysis model. When the type of medical data is time series data such as electrocardiograms, RNN (Recurrent Neural Network) can be selected as the initial analysis model. The global model parameters here can be the commonly used initial values of the model set according to experience.

[0077] Step 2: For each medical terminal, train the initial analysis model based on the local medical data of the medical terminal to obtain the local analysis model of the medical terminal, and send the local model parameters and loss function values of the local analysis model to the server. The local medical data matches the type of medical data and rare disease types.

[0078] For the medical terminals of different medical institutions A, B, C, D, and E respectively, the medical terminal starts to train the initial analysis model using the local medical data. The training methods such as the loss function and the number of iterations for training can be uniformly specified by the server, such as 5 times or 10 times per round, for a total of 10 rounds. For example, medical institution A inputs the coronary CTA image of patient a into the initial analysis model and trains it to output the probability value of patient a having the disease. Then medical institution B can input the coronary CTA image of patient b into the initial analysis model and train it to output the probability value of patient b having the disease, and so on, to obtain the local analysis models respectively.

[0079] After each round of iteration, each medical terminal can feedback the local model parameters and loss function values of the current local analysis model to the server, which can be specifically expressed as 、 、……、 ,where 、 、 、 are respectively multiple different sub-parameter items of the local analysis model, and Lost is the loss function value.

[0080] 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 terminal to update the model parameters of the initial analysis model in the medical terminal.

[0081] The server receives - Input into the particle swarm optimization model, such as Figure 2 shown, the particle swarm optimization model can output the optimized model parameters for each round in the following way: S100. Take the local model parameters sent by each medical end in this round as the position of particle i, and take the difference in the loss function of each medical end as the corresponding velocity of particle i.

[0082] Among them, the difference in the loss function is the difference between the loss function value sent by the medical end in this round and the average value of the loss function values in the previous round.

[0083] For each particle i, its position can be expressed as , ,..., .

[0084] For each particle i, its velocity can be expressed as = - , = - ,..., = - . Among them, is the average value of the loss function values corresponding to all medical ends in the previous round.

[0085] S101. Determine whether the convergence condition is satisfied.

[0086] The convergence condition here can be the number of iterations, etc.

[0087] And calculate the fitness value of each particle through the objective function, and compare it with the particle's optimal position to update the particle's optimal position.

[0088] S102. If not, update the position and velocity of each particle i, and return to execute the step of determining whether the convergence condition is satisfied.

[0089] In step S102, the position and velocity of each particle i can be updated in the following way: + + ( ); + ; Among them, is the updated velocity of particle i, is the velocity of particle i before update, is the updated position of particle i, is the position of particle i before update, is the particle optimal position of particle i, is the global optimal position, 、 is the learning parameter value (generally = = 2), 、 is the random parameter value, taking values in [0, 1], i = 1, 2, 3... N, and N is the total number of particles.

[0090] S103. If so, output the particle optimal position and the global optimal position of each particle i as the optimized model parameters.

[0091] Finally, when the convergence condition is met, the particle optimal position and the global optimal position of each particle i can be obtained.

[0092] Step Four: The server determines the optimized analysis model based on the optimized model parameters, and determines whether the optimized analysis model meets the preset conditions. If not, return to execute Step Two. If so, send the optimized analysis model to the target medical terminal; The server can use the optimized model parameters as the model parameters of the initial analysis model to determine the optimized analysis model. Then, it can calculate the accuracy of the optimized analysis model. When the accuracy meets the requirements, the iteration can be ended, and the obtained optimized analysis model is sent to the target medical terminal. When the accuracy does not meet the requirements, the optimized model parameters are fed back to each medical terminal to enable the medical terminal to continue iterative training.

[0093] Step Five: The target medical terminal inputs the medical data to be tested that matches the type of medical data into the optimized analysis model to obtain the analysis results corresponding to the rare disease types output by the optimized analysis model.

[0094] The target medical terminal can obtain the corresponding analysis results through the final optimized analysis model. Here, the optimized analysis model has higher accuracy and better generalization ability, thus playing a better auxiliary effect on the analysis of rare diseases.

[0095] For the communication process between Step One and Step Five, the SM2CBC algorithm can be used for encryption, and the key used in the encryption process can be generated by the method provided in the foregoing implementation.

[0096] In the embodiment of the present application, data encryption is performed on the training process of the rare disease analysis model, further protecting the security of rare disease data.

[0097] Embodiment Five In the embodiment of the present application, a rare disease data transmission method is provided. The communication nodes perform key distribution for the symmetric encryption algorithm through the following steps to perform encrypted transmission of rare disease medical data using the symmetric encryption algorithm: The sending communication node and the receiving communication node determine the modulus value and the original value of this node; 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 original value of this node 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 original value of this node 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 / 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 this key.

[0098] A rare disease data transmission method provided by an embodiment of the present application has the same technical effect as the rare disease data transmission system, and will not be elaborated here.

[0099] In the embodiments provided in the present application, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For another 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 coupling or direct coupling or communication connection shown or discussed with each other can be through some communication interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical, mechanical or other form.

[0100] In addition, the units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0101] Furthermore, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0102] It should be noted that if a function is implemented in the form of a software functional 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, in essence, or the part that contributes to the prior art or a part of this technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0103] In this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0104] The above are only the embodiments of the present application and are not used to limit the protection scope of the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A rare disease data transmission system, characterized in that, The system includes multiple communication nodes. The symmetric encryption algorithm is used for the transmission of rare disease medical data between the communication nodes. Among them, the key distribution of the symmetric encryption algorithm between the communication nodes is carried out through the following steps: The sending communication node and the receiving communication node determine the modulus value and the primitive root value; The sending communication node determines the first random value, and calculates the first exchange value based on the first random value, the modulus value and the primitive root value according to a preset algorithm; The receiving communication node determines the second random value, and calculates the second exchange value based on the second random value, the modulus value and the primitive root 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 / receiving communication node calculates the 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.

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 one of the medical end or the consultation end, the modulus value and the primitive root value are determined in the following manner: The server determines the modulus value and the primitive root value, and sends them to the medical end or the consultation end; When the sending communication node is one of the medical end and the consultation end, and the receiving communication node is the other of the medical end and the consultation end, the modulus value and the primitive root value are determined in the following manner: The server determines the modulus value and the primitive root value, and sends them to the medical end and the consultation end respectively.

3. The system according to claim 1, characterized in that, The communication node calculates the exchange value in the following manner: Calculates the first power value with the primitive root value as the base and the random value as the exponent; Calculates the remainder as the exchange value with the first power value as the dividend and the modulus value as the divisor.

4. The system according to claim 2, characterized in that, The communication node also includes an encryption calculation node. Based on the data level of the rare disease medical data, an encryption calculation node is added between the transmission links of the rare disease medical data, and the server determines the modulus value and the primitive root value, and sends them to each encryption calculation node.

5. The system according to claim 1, characterized in that, The communication node calculates the key in the following manner: Calculates the second power value with the received exchange value as the base and the local random value as the exponent; Calculates the remainder value with the second power value as the dividend and the modulus value as the divisor; Determines the key based on the remainder value, the exchange value and a preset relationship table.

6. The system according to claim 5, wherein The communication node is specifically used to determine the first English character in the preset relationship table with the remainder value as the abscissa and the first exchange value as the ordinate; Determines the second English character in the preset relationship table with the remainder value as the abscissa and the second exchange value as the ordinate; Generates multiple hexadecimal bytes based on the permutation and combination of the first exchange value, the second exchange value, the first English character and the second English character; Concatenates the multiple hexadecimal bytes in a specified order to generate a 128-bit key.

7. The system according to claim 1, characterized in that The server determines the modulus value in the following manner: Randomly generates a target value, and determines whether the target value is within a preset range; If so, determines the target value as the modulus value; If not, returns to execute the step of randomly generating the target value.

8. The system according to claim 7, characterized in that, The server determines the primitive root value greater than the determined modulus value.

9. The system according to claim 4, characterized in that, The communication node and the encryption calculation node set the key life cycle based on the data level of the rare disease medical data.

10. A method for transmitting rare disease data, characterized in that, The key distribution of the symmetric encryption algorithm between communication nodes is carried out through the following steps to encrypt and transmit rare disease medical data using the symmetric encryption algorithm: 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 / 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 the symmetric encryption algorithm based on the key.

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