CN113098891A - Method and system for network transmission control based on medical big data - Google Patents
Method and system for network transmission control based on medical big data Download PDFInfo
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Abstract
The invention discloses a method and a system for network transmission control based on medical big data, wherein the method comprises the following steps: constructing a medical big data edge calculation model; performing multistage anonymous access authentication on the intelligent health hardware equipment based on a medical big data edge computing model, wherein the intelligent health hardware equipment is dynamically accessed into edge computing equipment through a plug-and-play information model, and the edge computing equipment dynamically manages the intelligent health hardware equipment; the software control equipment distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method and issues a flow meter to each edge computing equipment; and each edge computing device performs time delay control of network transmission based on the flow meter. The embodiment of the invention achieves the effect of reducing the time delay, so that the energy consumption loss of the cloud platform system is reduced, and the load of the whole platform is reduced.
Description
Technical Field
The invention relates to the technical field of intelligent medical treatment, in particular to a method and a system for network transmission control based on medical big data.
Background
The cloud platform is the basis of internet application, and the 5G technology has the characteristics of large broadband and low time delay, reaches the bottleneck of internet application data transmission, and promotes the development of intelligent medical treatment to a higher level. Cloud medical systems, internet business systems and the like are used as cloud application systems, the internet of things is used as a smart sensing and executing system, and a big data platform and artificial intelligence are used as a smart medical central nervous system and are uniformly deployed on the cloud platform. Each service system of the intranet of the hospital is not only an execution system of the current service, but also a support system of the cloud platform service system, and the cloud platform service system and the intranet information system perform real-time data interaction to jointly realize intelligent acquisition, transmission, processing and application of data.
The data interaction frequency and the data interaction volume between the medical terminal and the cloud platform also rapidly increase along with the access of various types of equipment and the expansion of new services, and the transmission distance between the medical terminal and the platform is long, so that a large time delay is generated in the transmission process, the energy consumption loss of the whole cloud platform system is overlarge, and the load of the whole platform for calculating a large amount of data is overweight.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a method and a system for network transmission control based on medical big data, solves the problems of high processing delay of a cloud platform, high energy consumption loss and a load process caused by high processing delay of the cloud platform, and has the effect of reducing delay.
In order to solve the above problems, the present invention provides a method for controlling network transmission based on medical big data, wherein the method comprises:
constructing a medical big data edge calculation model, wherein the edge calculation model comprises: the intelligent health system comprises a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment, wherein the cloud server is used for gathering data of the software control equipment and performing high-level analysis related to big data, and the edge computing equipment is used for gathering the intelligent health hardware equipment; the software control equipment is used for centrally controlling the transmission of network information or scheduling network resources; the intelligent health hardware equipment is used for acquiring medical data and transmitting the medical data to the cloud server for data processing based on the edge computing equipment;
performing multistage anonymous access authentication on the intelligent health hardware equipment based on a medical big data edge computing model, wherein the intelligent health hardware equipment is dynamically accessed into edge computing equipment through a plug-and-play information model, and the edge computing equipment dynamically manages the intelligent health hardware equipment;
the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method based on the computing resources, the link transmission speed and the equipment load data of the current network, and sends a flow meter to each edge computing equipment;
and each edge computing device performs time delay control of network transmission based on the flow meter.
The method for distributing the required network computing tasks to each edge computing device by adopting the distributed computing method comprises the following steps:
and distributing required network computing tasks for each edge computing module by adopting a particle swarm optimization algorithm.
The software control equipment controls data transmission of the medical big data edge calculation model by adopting a lightweight data aggregation privacy protection method.
The software control equipment adopts a lightweight data aggregation privacy protection method to control data transmission of the medical big data edge calculation model, and the method comprises the following steps:
the intelligent health hardware equipment encrypts medical data by adopting a public key;
the edge computing equipment acquires the encrypted medical data, computes a medical data sharing value according to a safe multiparty computing (SMPC) protocol of the edge computing equipment, judges whether a decryption condition is met or not based on the medical data sharing value, and decrypts the encrypted medical data if the decryption condition is met;
after the software control equipment collects the data on the edge computing equipment, encrypting the decrypted medical data based on key encryption data distributed by a cloud server, and uploading the medical data encrypted based on the key encryption data to the cloud server;
the cloud server receives medical data encrypted based on the secret key, calculates a medical data shared value according to a safe multi-party calculation SMPC protocol of the cloud server, judges whether a decryption condition is met or not based on the medical data shared value, and decrypts the encrypted medical data if the decryption condition is met.
The intelligent health hardware device adopts a public key to encrypt the medical data, and the encryption comprises the following steps:
and carrying out binary number processing on the data acquired by the intelligent health hardware equipment, and carrying out bit-wise full homomorphic encryption processing on the binary number.
The edge computing device obtaining encrypted medical data comprises:
and the intelligent health hardware equipment adopts a lightweight packet recombination protocol to send encrypted medical data to the edge computing equipment.
The intelligent health hardware device comprises: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator.
Correspondingly, the embodiment of the invention also provides a system for controlling network transmission based on medical big data, which comprises:
the intelligent health system comprises a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment, wherein the cloud server is used for gathering data of the software control equipment and performing high-level analysis related to big data, and the edge computing equipment is used for gathering the intelligent health hardware equipment; the software control equipment is used for centrally controlling the transmission of network information or scheduling network resources; the intelligent health hardware equipment is used for acquiring medical data and transmitting the medical data to the cloud server for data processing based on the edge computing equipment;
the system constructs a medical big data edge computing model based on a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment;
the intelligent health hardware equipment is dynamically accessed to edge computing equipment through a plug-and-play information model, and the edge computing equipment dynamically manages the intelligent health hardware equipment;
the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method based on the computing resources, the link transmission speed and the equipment load data of the current network, and sends a flow meter to each edge computing equipment;
and each edge computing device performs time delay control of network transmission based on the flow meter.
The software control equipment controls data transmission of the medical big data edge calculation model by adopting a lightweight data aggregation privacy protection method.
The intelligent health hardware device comprises: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator.
According to the embodiment of the invention, by constructing the medical big data edge computing model, aiming at weaker computing capability than that of edge computing equipment, network global information is obtained through software control equipment, so that an optimal unloading scheme is worked out, network computing tasks are distributed to all the edge computing equipment, and the edge computing equipment realizes delay control of network transmission according to a corresponding flow table, so that the effect of reducing delay is achieved, the energy consumption loss of a cloud platform system is reduced, and the load of the whole platform is lightened.
According to the embodiment of the invention, a multi-level anonymous authentication mode is provided for the edge computing equipment by constructing the medical big data edge computing model, so that the re-authentication is not needed when the end equipment such as intelligent health hardware equipment and the like accesses the system, the complexity of the access of the end equipment is reduced, and the safety of the access of the medical hardware terminal is ensured. The data acquired by the intelligent health hardware equipment is encrypted and transmitted by adopting a fully homomorphic encryption technology, a lightweight packet reassembly protocol is introduced, the problem of excessive fragmentation of a data packet is solved, the encryption and decryption efficiency is optimized, and the security of controlling network transmission by the edge computing equipment is improved. Data aggregation is achieved through improved secure multi-party computing (SMPC), a shared key is used for computing a local shared value to update the key, data interaction between massive medical hardware terminals and a cloud server is reduced, and the broadband utilization rate in the data aggregation process is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic structural diagram of a system for network transmission control based on medical big data in an embodiment of the invention;
fig. 2 is a flowchart of a method for controlling network transmission based on medical big data in an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic structural diagram of a system for network transmission control based on medical big data in an embodiment of the present invention, where the system includes: cloud ware, edge computing device, software control equipment and a plurality of healthy hardware equipment of wisdom, wherein:
the cloud server is used for gathering data of the software control equipment and performing high-level analysis related to big data, and the edge computing equipment is used for gathering intelligent health hardware equipment; the software control equipment is used for centrally controlling the transmission of network information or scheduling network resources; the intelligent health hardware equipment is used for acquiring medical data and transmitting the medical data to the cloud server for data processing based on the edge computing equipment;
performing multistage anonymous access authentication on the intelligent health hardware equipment based on a medical big data edge computing model, wherein the intelligent health hardware equipment is dynamically accessed into edge computing equipment through a plug-and-play information model, and the edge computing equipment dynamically manages the intelligent health hardware equipment;
the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method based on the computing resources, the link transmission speed and the equipment load data of the current network, and sends a flow meter to each edge computing equipment;
and each edge computing device performs time delay control of network transmission based on the flow meter.
In a specific implementation process, the controlling, by the software control device, data transmission of the medical big data edge calculation model by using the lightweight data aggregation privacy protection method further includes: the software control equipment makes global computation unloading measurement based on the computation resources, link transmission speed and equipment load data of the current network, and issues flow tables to each edge computing equipment through an OpenFlow protocol.
In the specific implementation process, the computing resource of each edge computing device i is set to be Ci, each intelligent health hardware device transmits the total computing task D to the edge computing device i connected with the intelligent health hardware device,the edge computing device i divides the overall task D into Di＝δiD, and to each edge computing device (including itself). Thus, the total processing time of the total task D in the network is obtained as: t ═ max (δ)iD/Ci+Wi，jmi，j)+ts；
Wherein, deltaiD/CiRepresenting an edge computing device i to process a sub-task diTime of (W)i，jmi，jRepresenting the communication overhead between edge computing devices i and j, where mi，jWhen the value is 1, it indicates that the subtask allocation relationship exists, when the value is mi, and j is 0, it indicates that the subtask allocation relationship does not exist, and t s indicates that the software control device obtains the optimal unloading strategy and issues the time delay of the flow table.
The particle swarm optimization algorithm is adopted to distribute required network computing tasks for each edge computing module, and a computing unloading strategy is formulated, so that the convergence of the standard particle swarm optimization algorithm is improved, the local optimal problem is solved, the optimal computing unloading strategy is obtained, and the processing time delay of healthy big data is reduced.
The system is used for constructing a medical big data edge computing model based on a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment; performing multistage anonymous access authentication on the intelligent health hardware equipment based on a medical big data edge calculation model; the software control equipment controls data transmission of the medical big data edge calculation model by adopting a lightweight data aggregation privacy protection method.
The system provided by the embodiment of the invention is based on a cloud-edge computing network architecture, and the edge computing equipment can utilize equipment with computing and storage service functions at the edge of the network to endow computing and storage capacity for the access network, so that computer storage service can be provided by a user. The cloud-edge computing network structure is a platform which separates a data plane and a control plane of a traditional network device and performs centralized configuration and management on the network device through a centralized controller.
The cloud-edge computing network structure in the embodiment of the invention introduces a software control technology to realize a centralized control network and collect network global information on the basis of a traditional cloud platform, and simultaneously realizes safe acquisition and transmission of medical data through the computation-intensive operation of the edge computing technology in the edge processing of the network, such as a safe multi-party computing (SMPC) protocol between edge computing equipment and intelligent health hardware equipment, thereby ensuring the safety of data transmission.
In the specific implementation process, the intelligent health hardware equipment comprises: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator, and the intelligent health hardware can be connected to a network node at the edge through a wireless network or a limited network to access the network.
In the specific implementation process, a multi-level anonymous access authentication mode is adopted in the system for safety protection, encryption chips are configured on the edge computing equipment and the intelligent healthy hardware equipment, mutual identity authentication is required when the intelligent healthy hardware equipment is accessed into the edge computing equipment, and bidirectional identity authentication is also required when the edge computing equipment is accessed into the cloud server. Typically, the intelligent health hardware device only needs to mutually authenticate with the edge computing device and establish a session key. And after the access authentication is finished, carrying out data security transmission in the system by adopting a lightweight data aggregation privacy protection method.
In a specific implementation process, the edge computing device has a device composition with limited computing and storage capabilities, can forward data of the smart hardware device, the cloud server and the edge computing device, and can run an OpenFlow protocol. In the medical big data processing process, the intelligent hardware equipment firstly sends the acquired health data to the corresponding edge computing equipment for processing, the cosine of the edge computing processing stores the analysis result of the health big data, the health data is compared with the health data received by the terminal for calculation, then the health data from the terminal is stored, and the stored data and the diagnosis data are uploaded to the cloud server, so that the global sharing of information is realized. When the cloud computing platform is insufficient in resources, computing or storage can be performed through the edge computing device, so that the problem of insufficient computing resources is solved.
In a specific implementation process, the intelligent health hardware device sends encrypted medical data to the edge computing device by adopting a lightweight packet reassembly protocol.
In a specific implementation process, the intelligent health hardware equipment encrypts medical data by adopting a public key; the edge computing equipment acquires the encrypted medical data, computes a medical data sharing value according to a safe multiparty computing (SMPC) protocol of the edge computing equipment, judges whether a decryption condition is met or not based on the medical data sharing value, and decrypts the encrypted medical data if the decryption condition is met; after the software control equipment collects the data on the edge computing equipment, encrypting the decrypted medical data based on key encryption data distributed by a cloud server, and uploading the medical data encrypted based on the key encryption data to the cloud server; the cloud server receives medical data encrypted based on the secret key, calculates a medical data shared value according to a safe multi-party calculation SMPC protocol of the cloud server, judges whether a decryption condition is met or not based on the medical data shared value, and decrypts the encrypted medical data if the decryption condition is met. The data security in the process of acquiring and uploading medical big data to the cloud server is ensured through multi-level encryption, and the data is not easy to tamper.
In a specific implementation process, the encrypting the medical data by the intelligent health hardware device by using the public key includes: and carrying out binary number processing on the data acquired by the intelligent health hardware equipment, and carrying out bit-wise full homomorphic encryption processing on the binary number.
In a specific implementation, the obtaining, by the edge computing device, the encrypted medical data includes: and the intelligent health hardware equipment adopts a lightweight packet recombination protocol to send encrypted medical data to the edge computing equipment.
The intelligent health hardware device comprises: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator.
In a specific implementation process, the controlling, by the software control device, data transmission of the medical big data edge calculation model by using the lightweight data aggregation privacy protection method further includes: the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, and controls the medical data to be uploaded to the cloud server based on the computing resources, the link transmission speed and the equipment load data of the current network.
Fig. 2 is a flowchart illustrating a method for controlling network transmission based on medical big data in an embodiment of the present invention, where the method specifically includes:
s21, constructing a medical big data edge calculation model;
here, the edge calculation model includes: the intelligent health system comprises a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment, wherein the cloud server is used for gathering data of the software control equipment and performing high-level analysis related to big data, and the edge computing equipment is used for gathering the intelligent health hardware equipment; the software control equipment is used for centrally controlling the transmission of network information or scheduling network resources; the intelligent health hardware equipment is used for acquiring medical data and transmitting the medical data to the cloud server for data processing based on the edge computing equipment.
The cloud-edge computing network structure in the embodiment of the invention introduces a software control technology to realize a centralized control network and collect network global information on the basis of a traditional cloud platform, and simultaneously realizes safe acquisition and transmission of medical data through the computation-intensive operation of the edge computing technology in the edge processing of the network, such as a safe multi-party computing (SMPC) protocol between edge computing equipment and intelligent health hardware equipment, thereby ensuring the safety of data transmission.
S22, performing multistage anonymous access authentication on the intelligent health hardware equipment based on a medical big data edge calculation model;
it should be noted that the intelligent health hardware device dynamically accesses to the edge computing device through the plug and play information model, and the edge computing device dynamically manages the intelligent health hardware device.
S23, the software control equipment adopts a distributed computing method to distribute required network computing tasks for each edge computing equipment and issues a flow meter to each edge computing equipment;
the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method based on the computing resources, the link transmission speed and the equipment load data of the current network, and sends a flow meter to each edge computing equipment;
in the specific implementation process, the computing resource of each edge computing device i is set to be Ci, each intelligent health hardware device transmits the total computing task D to the edge computing device i connected with the intelligent health hardware device, and the edge computing device i divides the total task D into Di＝δiD, and to each edge computing device (including itself). Thus, the total processing time of the total task D in the network is obtained as: t ═ max (δ)iD/Ci+Wi，jmi，j)+ts；
Wherein, deltaiD/CiRepresenting an edge computing device i to process a sub-task diTime of (W)i，jmi，jRepresenting the communication overhead between edge computing devices i and j, where mi，jWhen the value is 1, it indicates that the subtask allocation relationship exists, when the value is mi, and j is 0, it indicates that the subtask allocation relationship does not exist, and t s indicates that the software control device obtains the optimal unloading strategy and issues the time delay of the flow table.
The particle swarm optimization algorithm is adopted to distribute required network computing tasks for each edge computing module, and a computing unloading strategy is formulated, so that the convergence of the standard particle swarm optimization algorithm is improved, the local optimal problem is solved, the optimal computing unloading strategy is obtained, and the processing time delay of healthy big data is reduced.
And S24, each edge computing device performs time delay control of network transmission based on the flow meter.
It should be noted that, the software control device herein controls data transmission of the medical big data edge calculation model by using a lightweight data aggregation privacy protection method.
It should be noted that, here, the controlling, by the software control device, data transmission of the medical big data edge calculation model by using the lightweight data aggregation privacy protection method includes: the intelligent health hardware equipment encrypts medical data by adopting a public key; the edge computing equipment acquires the encrypted medical data, computes a medical data sharing value according to a safe multiparty computing (SMPC) protocol of the edge computing equipment, judges whether a decryption condition is met or not based on the medical data sharing value, and decrypts the encrypted medical data if the decryption condition is met; after the software control equipment collects the data on the edge computing equipment, encrypting the decrypted medical data based on key encryption data distributed by a cloud server, and uploading the medical data encrypted based on the key encryption data to the cloud server; the cloud server receives medical data encrypted based on the secret key, calculates a medical data shared value according to a safe multi-party calculation SMPC protocol of the cloud server, judges whether a decryption condition is met or not based on the medical data shared value, and decrypts the encrypted medical data if the decryption condition is met.
It should be noted that the SMPC calculation process here is as follows: when n intelligent health hardware devices participate, all the calculations are in a finite field ZpWherein p is a prime number. Privacy secret r of intelligent health hardware device iiSelecting a unique point x other than zeroi∈ZpAnd is selected to have fi(0)＝riRandom secret sharing polynomial fi(x) Its unique point xiSend to all other intelligent health hardware devices and receive the shared value f calculated by the other (n-1) intelligent health hardware devicesj(xi) Then calculate
The steps are completed by all intelligent healthy hardware equipment and are obtained by calculationF (x) ofi) The values are sent up to an edge computing device, which utilizes F (x)m) The value and Lagrange interpolation constructs an (n-1) degree polynomial h (x), wherein m is subject to {1, … n }, and constant terms of h (x) are a set of all intelligent health hardware device secrets governed by the edge computing device.
It should be noted that the encrypting the medical data by the intelligent health hardware device using the public key includes: and carrying out binary number processing on the data acquired by the intelligent health hardware equipment, and carrying out bit-wise full homomorphic encryption processing on the binary number. Data of the intelligent health hardware device is encrypted through the distributed public key before being sent. The public key is generated by adopting a Smart-Vercauteren (SV) method based on fully homomorphic encryption, wherein the SV method consists of five algorithms of KeyGen, Enc, Dec, Add and Multiply, and the method comprises the following steps of: KeyGen (lambda) is a key generation algorithm, and generates a required private key and a required public key according to an input security parameter lambda; enc (PK, m) is an encryption algorithm, and a plaintext m is encrypted by using a public key PK to obtain a ciphertext c; dec (SK, c) is a decryption algorithm, which decrypts ciphertext using a private key SK to obtain plaintext.
It should be noted that the obtaining of the encrypted medical data by the edge computing device includes: and the intelligent health hardware equipment adopts a lightweight packet recombination protocol to send encrypted medical data to the edge computing equipment. The intelligent health hardware equipment sends the encrypted data to the edge computing equipment in the area, a lightweight packet reassembly protocol is adopted in the transmission process, the lightweight packet reassembly protocol enables the cloud-edge computing network to enable the intelligent health hardware equipment to add a minimum header containing the size of a data packet at a sending end of a section reassembly protocol, and the process of grouping and reassembling the data packet is simplified by reading the size of the data packet and collecting data with corresponding size. And a lightweight hash function is adopted in the lightweight packet reassembly protocol, so that the operation pressure of intelligent healthy hardware equipment in the cloud-edge computing network is reduced, and synchronous errors among the intelligent healthy hardware equipment can be processed by using a sliding address window.
It should be noted that the intelligent health hardware device includes: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator.
It should be noted that the software control device, which controls data transmission of the medical big data edge calculation model by using the lightweight data aggregation privacy protection method, further includes: the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, and controls the medical data to be uploaded to the cloud server based on the computing resources, the link transmission speed and the equipment load data of the current network.
It should be noted that the software control device, which controls data transmission of the medical big data edge calculation model by using the lightweight data aggregation privacy protection method, further includes: the software control equipment makes global computation unloading measurement based on the computation resources, link transmission speed and equipment load data of the current network, and issues flow tables to each edge computing equipment through an OpenFlow protocol, so that the controllability of network transmission is guaranteed, and the network delay characteristic is reduced.
According to the embodiment of the invention, by constructing the medical big data edge computing model, aiming at which computing equipment has weaker computing capability, the software control equipment is used for acquiring the network global information, so that an optimal unloading scheme is worked out, the network computing task is distributed to each edge computing equipment, and the edge computing equipment realizes the delay control of network transmission according to the corresponding flow table, so that the effect of reducing delay is achieved, the energy consumption loss of a cloud platform system is reduced, and the load of the whole platform is lightened.
According to the embodiment of the invention, a multi-level anonymous authentication mode is provided for the edge computing equipment by constructing the medical big data edge computing model, so that the re-authentication is not needed when the end equipment such as intelligent health hardware equipment and the like accesses the system, the complexity of the access of the end equipment is reduced, and the safety of the access of the medical hardware terminal is ensured. The data acquired by the intelligent health hardware equipment is encrypted and transmitted by adopting a fully homomorphic encryption technology, a lightweight packet reassembly protocol is introduced, the problem of excessive fragmentation of a data packet is solved, the encryption and decryption efficiency is optimized, and the security of controlling network transmission by the edge computing equipment is improved. Data aggregation is achieved through improved secure multi-party computing (SMPC), a shared key is used for computing a local shared value to update the key, data interaction between massive medical hardware terminals and a cloud server is reduced, and the broadband utilization rate in the data aggregation process is improved. The above embodiments of the present invention are described in detail, and the principle and the implementation of the present invention are described herein by using specific embodiments, and the description of the above embodiments is only used to help understanding the method of the present invention and the core idea thereof; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A method for network transmission control based on medical big data is characterized by comprising the following steps:
constructing a medical big data edge calculation model, wherein the edge calculation model comprises: the intelligent health system comprises a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment, wherein the cloud server is used for gathering data of the software control equipment and performing high-level analysis related to big data, and the edge computing equipment is used for gathering the intelligent health hardware equipment; the software control equipment is used for centrally controlling the transmission of network information or scheduling network resources; the intelligent health hardware equipment is used for acquiring medical data and transmitting the medical data to the cloud server for data processing based on the edge computing equipment;
performing multistage anonymous access authentication on the intelligent health hardware equipment based on a medical big data edge computing model, wherein the intelligent health hardware equipment is dynamically accessed into edge computing equipment through a plug-and-play information model, and the edge computing equipment dynamically manages the intelligent health hardware equipment;
the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method based on the computing resources, the link transmission speed and the equipment load data of the current network, and sends a flow meter to each edge computing equipment;
and each edge computing device performs time delay control of network transmission based on the flow meter.
2. The method for network transmission control based on medical big data according to claim 1, wherein the distributing the required network computing tasks to each edge computing device by using the distributed computing method comprises:
and distributing required network computing tasks for each edge computing module by adopting a particle swarm optimization algorithm.
3. The method for network transmission control based on medical big data as claimed in claim 2, wherein the software control device controls data transmission of the medical big data edge computing model by adopting a lightweight data aggregation privacy protection method.
4. The method for network transmission control based on medical big data according to claim 3, wherein the step of controlling data transmission of the medical big data edge calculation model by the software control device by adopting a lightweight data aggregation privacy protection method comprises the following steps:
the intelligent health hardware equipment encrypts medical data by adopting a public key;
the edge computing equipment acquires the encrypted medical data, computes a medical data sharing value according to a safe multiparty computing (SMPC) protocol of the edge computing equipment, judges whether a decryption condition is met or not based on the medical data sharing value, and decrypts the encrypted medical data if the decryption condition is met;
after the software control equipment collects the data on the edge computing equipment, encrypting the decrypted medical data based on key encryption data distributed by a cloud server, and uploading the medical data encrypted based on the key encryption data to the cloud server;
the cloud server receives medical data encrypted based on the secret key, calculates a medical data shared value according to a safe multi-party calculation SMPC protocol of the cloud server, judges whether a decryption condition is met or not based on the medical data shared value, and decrypts the encrypted medical data if the decryption condition is met.
5. The method for network transmission control based on big medical data as claimed in claim 4, wherein said intelligent health hardware device uses public key to encrypt the medical data comprises:
and carrying out binary number processing on the data acquired by the intelligent health hardware equipment, and carrying out bit-wise full homomorphic encryption processing on the binary number.
6. The method for network transmission control based on medical big data as claimed in claim 5, wherein the edge computing device obtaining the encrypted medical data comprises:
and the intelligent health hardware equipment adopts a lightweight packet recombination protocol to send encrypted medical data to the edge computing equipment.
7. The method for network transmission control based on big medical data as claimed in claim 6, wherein the intelligent health hardware device comprises: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator.
8. A system for network transmission control based on medical big data is characterized by comprising:
the intelligent health system comprises a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment, wherein the cloud server is used for gathering data of the software control equipment and performing high-level analysis related to big data, and the edge computing equipment is used for gathering the intelligent health hardware equipment; the software control equipment is used for centrally controlling the transmission of network information or scheduling network resources; the intelligent health hardware equipment is used for acquiring medical data and transmitting the medical data to the cloud server for data processing based on the edge computing equipment;
the system constructs a medical big data edge computing model based on a cloud server, edge computing equipment, software control equipment and intelligent health hardware equipment;
the intelligent health hardware equipment is dynamically accessed to edge computing equipment through a plug-and-play information model, and the edge computing equipment dynamically manages the intelligent health hardware equipment;
the software control equipment acquires the computing resources, the link transmission speed and the equipment load data of the current network, distributes required network computing tasks to each edge computing equipment by adopting a distributed computing method based on the computing resources, the link transmission speed and the equipment load data of the current network, and sends a flow meter to each edge computing equipment;
and each edge computing device performs time delay control of network transmission based on the flow meter.
9. The system for network transmission control under medical big data according to claim 8, wherein the software control device controls data transmission of the medical big data edge computing model by adopting a lightweight data aggregation privacy protection method.
10. The system for network transmission control based on big medical data as claimed in claim 9, wherein the intelligent health hardware device comprises: the intelligent health hardware equipment comprises an intelligent terminal, a digital medical terminal and a medical sensor, wherein the intelligent health hardware equipment uses the same shared secret key when governed by the same edge computing equipment, and the shared secret key is used as an initial number input value of a random number generator.
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