Medical data security sharing method based on data quality evaluation and Stackelberg profit driving

Abstract

The invention discloses a medical data security sharing method based on data quality evaluation and Stackelberg profit driving. The medical data security sharing method comprises the following four modules: a medical data requester MDR, an IoMT device, a block chain network and a cloud service. When the MDR initiates a request, the IoMT senses the data and then sends the data to the cloud service, and the cloud service performs data quality measurement and finally sends the data to the MDR. The invention provides a medical data security sharing framework oriented to an IoMT scene, integrates an attribute-based access control smart contract, an IoMT data quality multi-dimensional evaluation method and a Stackelberg game incentive mechanism, and cooperatively solves the core problems of authority management, security guarantee, incentive optimization and the like in medical data sharing.

Description

Technical Field

[0001] This invention relates to a method for secure sharing of medical data based on data quality assessment and Stackelberg's profit-driven approach. Background Technology

[0002] The Internet of Things in Healthcare (IoMT) is of great significance to the digital construction and development of the healthcare field, but it also faces many challenges. Existing blockchain-based healthcare data sharing models neglect the issue of the sharer's benefit, resulting in insufficient willingness to share and severely hindering further improvements in sharing efficiency. First, while most patients are willing to share their medical data, this sharing needs to be based on receiving compensation. Second, there are privacy and security challenges in healthcare data sharing. Healthcare data is inherently sensitive patient information, and both patients and hospitals are concerned about the security of healthcare data sharing systems, making them unwilling to share data.

[0003] To address the challenges of willingness to share medical data, incentive mechanisms can be introduced to stimulate the sharing willingness of patients and medical institutions, thereby encouraging IoMT users and medical institutions to participate in the IoMT data market and promoting the circulation of IoMT data. Regarding the privacy and security challenges of medical data sharing, strict access control mechanisms can be established to construct privacy protection methods for IoMT data. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention proposes a secure medical data sharing method based on data quality assessment and Stackelberg profit-driven principles, aiming to enhance the willingness and efficiency of medical data sharing. First, this method proposes an attribute-based access control smart contract to ensure security during the IoMT data sharing process. Second, a data quality assessment mechanism is designed to ensure the quality of IoMT data sharing. Finally, a game-theoretic incentive model is introduced to optimize the distribution of participant rewards, maximizing profits between the IoMT and participating users. Simulation results show that the proposed scheme demonstrates good performance in terms of contract performance, QoD assessment accuracy, and incentive effects, and can improve medical data sharing to a certain extent.

[0005] To achieve the above objectives, the medical data secure sharing method based on data quality assessment and Stackelberg profit-driven principles described in this invention comprises the following four modules:

[0006] ① A Medical data requester (MDR) is a healthcare worker who initiates a request to share medical data. When an MDR has a data sharing need, they need to apply to the system for sharing permissions and pay a deposit to obtain them.

[0007] Medical data;

[0008] ②IoMT devices refer to medical data sensing devices in the system. When the MDR initiates a data sharing request, the IoMT device...

[0009] Prepare to provide medical data;

[0010] ③ Blockchain Network: Blockchain refers to the underlying network of the system, responsible for storing and recording MDR data request records.

[0011] Smart contracts for data sharing, transaction authorization, etc.;

[0012] ④ Cloud services: Virtualize and allocate physical hardware resources on demand, and are responsible for measuring the data quality of medical data sensed by IoMT devices;

[0013] The medical data requester (MDR) requests sharing permissions from the system, and its permission control includes: Registration Contract (RC), Access Control Contract (ACC), Decision Contract (JC), and Audit Log Contract (ALC).

[0014] The process by which the IoMT device provides medical data to achieve MDR data sharing includes the following four steps:

[0015] Step-1: MDR initiates a data sharing request and pays a deposit. The ABAC smart contract ABAC-SCs grants access control authorization to MDR. After obtaining the authorization, ALC records the authorization result.

[0016] Step 2: ALC obtains the authorization result and sends the execution task to IoMT;

[0017] Step-3: After the IoMT sensing is completed, the results are fed back to the DS-SCs and metadata is sent to the cloud service. The DS-SCs record the sensing results and the cloud service measures the data quality.

[0018] Step-4: After the cloud service receives the metadata, it performs quality assessment on the medical data provided by the IoMT device and sends the assessment results back to AL-SC for recording. At the same time, the assessment results and metadata are sent to MDR.

[0019] The cloud service measures data quality by judging the accuracy, completeness, authenticity, and timeliness of medical data.

[0020] Preferably, a Stackelberg incentive mechanism is also introduced, then the overall profit maximization formula of the Stackelberg game is as follows:

[0021]

[0022] Where α is the ratio of the actual amount of data obtained to the ideal amount of data, and the specific calculation formula is as follows:

[0023] Where, N act N represents the actual amount of data obtained. ide Indicates the ideal data volume;

[0024] β is the QoD of the IoMT device. QoD refers to the suitability of the data to meet its intended use.

[0025] It is the partial derivative of α, β * It is the partial derivative of β;

[0026] F s ( ) is the utility function of MDR, which can be defined as:

[0027] F s (α,β)=k1arctan(αβγη i )-[(1-α)βγC1+σ];

[0028] Where k1 is the curve fitting parameter, used to simulate the change in returns under real-world conditions, and satisfies k1∈(0,1); γ represents the data scale, C1 represents the computational cost, and σ represents the computational resources consumed in running the smart contract; η i For the timeliness of medical data, the following condition must be met: 1 ≥ η1 > η2 > ... > η k >0, and i = 1, 2, ..., k.

[0029] The utility function for each IoMT can be defined as:

[0030] G t (α i )=k2arctan(α i γ i η i )-α i γ i C2;

[0031] Where k2 is the curve fitting parameter used to simulate the change in returns under real-world conditions, and satisfies k1∈(0,1); C2 represents the computational cost required by the IoMT device to capture this medical data. In the complete data sharing process, all α... i and γ i Together they constitute α and γ;

[0032] By analyzing G t (α i ,γ i Regarding α i Find the partial derivatives

[0033]

[0034] Where C1 represents the computational cost, and k1 is the curve fitting parameter used to simulate the changes in returns under real-world conditions.

[0035] Preferably, the cloud service judges the accuracy, completeness, authenticity, and timeliness of medical data according to the following formula: The formula for calculating accuracy is:

[0036]

[0037] Where D anom It is an outlier; D All It is the total amount of all perceived medical data;

[0038] The formula for calculating integrity is:

[0039]

[0040] Among them, D miss Indicates missing values ​​in medical data;

[0041] The formula for calculating authenticity is:

[0042]

[0043] Where ε represents the quantified value of environmental factors, and satisfies 0≤ε≤1. This represents the energy consumption of an IoMT device, and satisfies 0 ≤

[0044]

[0045] The timeliness of medical data is determined when the MDR obtains the data, denoted as η. i And satisfying 1≥η1>η2>…>η k If the result is greater than 0, then the sum of the four attributes affecting QoD, x, can be obtained. i The calculation formula is:

[0046] x i =Acc i +Comp i +Real i +η i .

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] ① An ABAC smart contract system suitable for medical data sharing was proposed, and smart contracts for registration, access control, decision-making, and audit logs were designed. These contracts cooperate to complete the authorization process, ensuring the security of IoMT data sharing and circulation.

[0049] ② A multidimensional QoD assessment model for the IoMT environment was constructed to quantify the accuracy, completeness, authenticity and timeliness of medical data, and the quality score was dynamically updated in combination with historical data.

[0050] ③ A Stackelberg game model based on data quality and data ratio was designed to achieve optimal profit allocation between medical data requesters and providers, thereby stimulating the willingness to share data. Attached Figure Description

[0051] Figure 1 The system architecture of this invention is as follows:

[0052] Figure 2 For: Blockchain-based IoMT sharing solution Detailed Implementation

[0053] The present invention will now be described in further detail with reference to specific embodiments.

[0054] The medical data secure sharing method based on data quality assessment and Stackelberg profit-driven principles described in this invention comprises the following components.

[0055] I. System Architecture

[0056] ① Medical data requester: A medical data requester (MDR) is a healthcare worker who initiates a request for medical data sharing, including doctors, nurses, pharmacists, and hospital researchers. When an MDR needs medical data, they only need to apply for sharing permissions from the system and pay a deposit to obtain the medical data to meet their needs such as case analysis.

[0057] ② IoMT Devices: IoMT devices refer to the medical data sensing devices in the system, including sensors, monitoring equipment, and smart cameras. When the MDR initiates a data sharing request, the IoMT device is responsible for sensing high-quality medical data from the patient to meet the MDR's data needs and generate revenue. Due to the severely limited computing resources of IoMT devices, the system only needs to ensure the security of medical data and incentivize devices to share it. Furthermore, all medical data sharing processes are recorded on the blockchain to ensure the traceability of medical data circulation.

[0058] ③ Blockchain Network: Blockchain refers to the underlying network in the system, responsible for storing MDR's data request records and running smart contracts for data sharing, transaction authorization, etc. When MDR initiates a data sharing request, it interacts with the blockchain's smart contracts to complete the sharing of medical data.

[0059] ④ Cloud Services: Cloud services refer to a service model that provides computing resources via the Internet. Its core lies in virtualizing physical hardware resources and allocating them on demand, allowing users to access the services they need without directly managing the underlying infrastructure. Since IoMT devices have limited computing resources, cloud services are responsible for measuring the data quality of the medical data sensed by the IoMT devices.

[0060] II. Access Control

[0061] To prevent the system's Medical Data Provider (MDR) from initiating unauthorized medical data sharing requests and to protect the system from sensitive information leakage, we have developed an ABAC (Automatic Guided Access) system for authorizing MDR requests. Specifically, we define the ABAC strategy using a quadruple, as shown in (1):

[0062] ABAC={Target,Object,Rule,E} (1)

[0063] Target represents the subject of the attribute, that is, the attribute possessed by the MDR that actively initiates the sharing request; Object represents the object of the attribute, that is, the attribute possessed by all IoMT devices that may meet the medical data needs of the MDR; Rule represents the ABAC policy rule; E represents the environmental attribute describing the access process.

[0064] We leveraged the automatic execution feature of smart contracts to develop four ABAC smart contracts (ABAC-SCs), including a Registration Contract (RC), an Access Control Contract (ACC), a Decision Contract (JC), and an Audit Log Contract (ALC). The specific functions of these smart contracts are shown in Table 1.

[0065] Table 1 - Specific Functions of ABAC-SCs

[0066]

[0067] ACC: Primarily implements request control (authorization or denial) for MDRs and is a core component of ABAC-SCs. When an MDR requests shared data, the system calls this method to encapsulate the attributes and invokes the policy addition method of PMC to obtain permission. 1) Request Control Decision: ACC can verify whether an MDR has the request permission and monitor its request frequency to prevent malicious behavior. 2) Policy Management: ACC can dynamically add, delete, and modify MDR access policies. 3) Behavior Monitoring: ACC can monitor access frequency and patterns in real time. 4) Anomaly Detection: ACC can automatically identify suspicious behavior and trigger penalties.

[0068] RC: Primarily implements contract registration functionality in ABAC and is an important component of ABAC-SCs. 1) Contract Registration: RC can register Access Control Contracts (ACC) and Judgment Contracts (JC). 2) Information Management: RC can store complete information such as contract address, ABI, and creator. 3) Search Service: Contract addresses and ABIs can be quickly searched via ACC. 4) Update and Maintenance: RC supports dynamic updates of contract information.

[0069] JC: Primarily implements the decision-making function in ABAC and is an important component of ABAC-SCs. 1) Penalty Algorithm: JC penalizes violations based on the MDR's violation records; the more violations, the more severe the penalty. 2) Event Notification: Each decision by JC triggers an event for easy monitoring.

[0070] ALC: Primarily implements event logging functionality during the ABAC authorization process, including access request logging, authorization logging, behavior logging, policy management logging, and contract registration logging. It is a component of ABAC-SCs.

[0071] We describe the execution flow of the access control contract as an algorithm, as shown in Algorithm 1:

[0072]

[0073] III. Medical Data Sharing Process

[0074] The automatic execution capability of smart contracts allows us to automate and track certain state transitions within the blockchain. Through smart contracts deployed on the blockchain, we can complete the entire process from IoMT data perception to MDR obtaining medical data.

[0075] The MDR request for IoMT-sensed data is a core component of medical data sharing. When the MDR initiates a request, the IoMT senses the data, sends it to the cloud service, performs data quality assessment, and finally sends it back to the MDR. The specific process is as follows: Figure 2 As shown:

[0076] Step 1: The MDR initiates a data sharing request and pays a deposit. ABAC-SCs perform access control authorization on the MDR, and after obtaining permissions, AL-SC records the authorization result.

[0077] Step 2: DS-SCs obtain the authorization result and send the execution task to IoMT. The core algorithm of DS-SCs is shown in Algorithm 2.

[0078] Step 3: IoMT Data Sensing. After IoMT sensing is completed, the results are fed back to ALC and metadata is sent to the cloud service. ALC records the sensing results, and the cloud service measures the data quality.

[0079] Step 4: Data Quality Assessment. After receiving the metadata, the cloud service performs quality assessment on the medical data provided by the IoMT device, and sends the assessment results back to AL-SC for recording. At the same time, the assessment results and metadata are sent to MDR.

[0080] It is worth noting that all IoMT data sharing processes within the system are encrypted. Only the requesting MDR and the data provider possess the decryption key, meaning they have the capability to decrypt the original data. Therefore, even if data is intercepted, it cannot cause substantial damage, greatly enhancing the system's data security.

[0081] IV. Data Quality Assessment of IoMT

[0082] In the model proposed in this invention, two main participating entities are considered: IoMT devices and MDRs. MDRs publish data requests, while IoMT devices provide medical data to MDRs. Within IoMT devices, medical data carries core information such as patient diagnoses, treatment plans, medication records, and medical imaging results. Typically, the accuracy, completeness, authenticity, and timeliness of medical data are the most important dimensions for measuring Quality of Delivery (QoD). Therefore, IoMT devices need to provide accurate, complete, and authentic medical data to MDRs in a timely manner to maintain their credibility.

[0083] Let the total number of members be M, and define the IoMT device set T. I ={t1,t2,…,t i}, MDR set S J ={s1,s2,…,s j}, where M = T I ∪S J Suppose that the attributes of medical data are represented by a set D. attr ={d attr1 ,d attr2 ,…,d attrn The medical dataset is composed of [data structure], and the missing data attribute is D. lack ={d lack1 ,d lack2 ,…,d lackn Then, the evaluation function for medical data can be expressed as:

[0084]

[0085] The QoD of an IoMT device includes attributes such as accuracy, completeness, authenticity, and timeliness. Timeliness is determined when the IoMT device provides data to the MDR, while accuracy, completeness, and authenticity are obtained through calculation.

[0086] Medical data accuracy refers to the precision with which IoMT devices perceive medical data, including outliers D. anom (isolated, erroneous values) and other correctly perceived data. According to formula (1), the formula for calculating the accuracy of medical data is:

[0087]

[0088] Among them, D All This refers to the total amount of all perceived medical data.

[0089] Medical data integrity refers to the ratio of collected medical data to the actual medical data required for MDR (Medical Data Retrieval). According to formula (1), the formula for calculating medical data integrity is:

[0090]

[0091] Among them, D miss This indicates missing values ​​in medical data.

[0092] The authenticity of medical data is affected by the physical characteristics of IoMT devices themselves, including environmental factors and energy consumption. For example, weather conditions and the power consumption of the IoMT can affect its operation. The formula for calculating the authenticity of medical data is:

[0093]

[0094] Where ε represents the quantified value of environmental factors, and satisfies 0≤ε≤1. This indicates the energy consumption of the IoMT device, and satisfies...

[0095] Medical data timeliness refers to the timely arrival of the data required by the Medical Data Provider (MDR), determined when the MDR obtains the data, and is denoted as η. i And satisfying 1≥η1>η2>…>η k >0.

[0096] The accuracy, completeness, authenticity, and timeliness of medical data positively impact the QoD of IoMT devices. In other words, the higher the QoD score of an IoMT device, the more timely, accurate, complete, and authentic its medical data. To accurately assess the QoD of the medical data provided by each IoMT, we define the sum of the four attributes affecting QoD as x. i Then we can get x i The calculation formula is:

[0097] x i =Acc i +Comp i +Real i +ηi (6)

[0098] Obviously, different x i Different factors have different impacts on the QoD of IoMT devices, therefore, x i The quality rating function is defined as follows:

[0099]

[0100] Among them, θ1, θ2, θ3, and θ4 are x that react differently. i The constants (θ1, θ2 < 0, and θ1 < θ2; θ3, θ4 > 0, and θ3 < θ4) are defined as shown in Table 2:

[0101]

[0102]

[0103] To accurately assess the QoD of each IoMT device, each IoMT device can have its quality score continuously updated using a rating function. The QoD of an IoMT device can be expressed as:

[0104]

[0105] Where ρ represents the characteristic of a rapid increase in QoD when an IoMT device generates high-quality data, h i This represents the historical rating of the IoMT device, φ represents a data constant, and χ represents the number of times the IoMT device provided low-quality medical data. QoD i It has the following characteristics:

[0106] ①QoD i The value decreases as IoMT devices continue to provide low-quality medical data.

[0107] ②QoD i The number of cases increases slowly as IoMT continues to provide high-quality medical data. However, once IoMT devices provide low-quality medical data, the number of cases increases. i The value will decrease rapidly.

[0108] V. Stackelberg-based incentive mechanism

[0109] This section will further examine the profit distribution between IoMT devices and MDRs in the process of medical data sharing, to ensure that IoMTs can continuously provide high-quality medical data. Generally, balancing the profit distribution among participants is crucial for achieving sustainable medical data sharing transactions. Stackelberg game theory is particularly suitable for the leader-follower model, where the MDR, as the leader, publishes medical data demands and prices them according to the market, while the IoMT device provides high-quality medical data to earn revenue. Therefore, this section will introduce Stackelberg game theory to construct the game between the two parties to maximize profits.

[0110] The medical data obtained by MDR is affected by the actual amount of data acquired, the QoD of the IoMT device, and the data scale. There is a certain difference between the ideal data volume and the actual amount of data acquired; we define this as the actual data acquisition ratio, and its calculation formula can be expressed as:

[0111]

[0112] Where, N act N represents the actual amount of data obtained. ide Let α represent the ideal data volume. The QoD of an IoMT device is defined as β. Generally, the benefit of MDR (Mean Direct Response) is positively correlated with α and β; that is, the closer the data is to the ideal, the higher the QoD (or the more reliable the IoMT device), the higher the benefit of MDR. Conversely, under equal α and β conditions, the smaller the time factor (the greater the time cost of IoMT sensing data), the lower the benefit of MDR, meaning the IoMT device fails to provide effective data in a timely manner. Therefore, the utility function of MDR can be defined as:

[0113] F s (α,β)=k1arctan(αβγη i )-[(1-α)βγC1+σ] (10)

[0114] Where k1 is the curve fitting parameter used to simulate the changes in returns under real-world conditions. γ represents the data size, C1 represents the computational cost, and σ represents the computational resources consumed in running the smart contract.

[0115] The goal of IoMT devices is to perceive as much medical data as possible required by MDR (Medical Research Center) while ensuring the Quality of Medical Data (QoD) of medical data, and proactively provide MDR with complete medical data to generate revenue. For each IoMT device, its revenue primarily comes from the reward for providing medical data to MDR, while the cost depends on the scale γ of the medical data generated. Therefore, the utility function of each IoMT can be defined as:

[0116] G t (α i)=k2arctan(α i γ i η i )-α i γ i C2 (11)

[0117] Where k2 is the curve fitting parameter used to simulate changes in returns under real-world conditions. C2 represents the computational cost required by the IoMT device to capture this medical data. Throughout the complete data sharing process, all α... i and γ i Together they constitute α and γ.

[0118] Assume that the medical data sensed by the IoMT device follows a data acquisition ratio strategy, meaning that the medical data sensed by the IoMT device should meet the data requirements of MDR (Medical Data Retrieval) as much as possible. Therefore, the IoMT device can maximize its own benefits by determining the maximum data acquisition ratio. This can be achieved by analyzing G... t (α i ,γ i Regarding α i Taking the partial derivative, we get:

[0119]

[0120] The ultimate goal of MDR is to acquire high-quality medical data; therefore, it follows a QoD (Quality of Health and Well-being) strategy to maximize its own benefit. Substituting equation (10) into equation (7), we can obtain the utility function F of MDR. s (α * (β,γ). For F s (α * Taking the first and second partial derivatives of F with respect to β, we can find that: when F s (α * When ,β,γ)>0, the function is strictly concave and has an extreme point β. * :

[0121]

[0122] Therefore, MDR can obtain the maximum profit when it is in a leader position in the Stackelberg game. In the scheme proposed in this invention, the overall profit maximization formula for the Stackelberg game is as follows:

[0123]

[0124] The above description is only a part of the specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A healthcare data security sharing approach based on data quality assessment and Stackelberg's profit-driven model, comprising the following four modules: ① A Medical data requester (MDR) is a healthcare worker who initiates a request to share medical data. When an MDR has a need to share data, they need to apply to the system for sharing permissions and pay a deposit in order to obtain the medical data. ②IoMT devices refer to medical data sensing devices in the system. When the MDR initiates a data sharing request, the IoMT device provides medical data. ③ Blockchain network: Blockchain refers to the underlying network of the system, which is responsible for storing MDR data request records and running smart contracts such as data sharing and transaction authorization; ④ Cloud services: Virtualize and allocate physical hardware resources on demand, and are responsible for measuring the data quality of medical data sensed by IoMT devices; The medical data requester (MDR) requests sharing permissions from the system, and its permission control includes: Registration Contract (RC), Access Control Contract (ACC), Decision Contract (JC), and Audit Log Contract (ALC). The process by which the IoMT device provides medical data to achieve MDR data sharing includes the following four steps: Step-1: MDR initiates a data sharing request and pays a deposit. The ABAC smart contract ABAC-SCs grants access control authorization to MDR. After obtaining the authorization, ALC records the authorization result. Step 2: ALC obtains the authorization result and sends the execution task to IoMT; Step-3: After the IoMT sensing is completed, the results are fed back to ALC and metadata is sent to the cloud service. ALC records the sensing results and the cloud service measures the data quality. Step-4: After the cloud service receives the metadata, it performs quality assessment on the medical data provided by the IoMT device and sends the assessment results back to AL-SC for recording. At the same time, the assessment results and metadata are sent to MDR. The cloud service measures data quality by judging the accuracy, completeness, authenticity, and timeliness of medical data.

2. The medical data secure sharing method based on data quality assessment and Stackelberg profit-driven model according to claim 1, characterized in that: Furthermore, by introducing the Stackelberg incentive mechanism, the overall profit maximization formula for the Stackelberg game is as follows: Where α is the ratio of the actual amount of data obtained to the ideal amount of data, and the specific calculation formula is as follows: Where, N act N represents the actual amount of data obtained. ide Indicates the ideal data volume; β is the QoD of the IoMT device. QoD refers to the suitability of the data to meet its intended use. It is the partial derivative of α, β * It is the partial derivative of β; F s ( ) is the utility function of MDR, which can be defined as: F s (α,β)=k1arctan(αβγη i )-[(1-α)βγC1+σ]; Where k1 is the curve fitting parameter, used to simulate the change in returns under real-world conditions, and satisfies k1∈(0,1); γ represents the data scale, C1 represents the computational cost, and σ represents the computational resources consumed in running the smart contract; η i For the timeliness of medical data, the following condition must be met: 1 ≥ η1 > η2 > ... > η k >0, i = 1, 2, ..., k; The utility function for each IoMT can be defined as: G t (a i )=k2arctan(α i c i or i )-a i b i C2; Where k2 is the curve fitting parameter used to simulate the change in returns under real-world conditions, and satisfies k1∈(0,1); C2 represents the computational cost required by the IoMT device to capture this medical data. In the complete data sharing process, all α... i and γ i Together they constitute α and γ; By analyzing G t (α i ,γ i Regarding α i Find the partial derivatives Where C1 represents the computational cost, and k1 is the curve fitting parameter used to simulate the changes in returns under real-world conditions.

3. The medical data secure sharing method based on data quality assessment and Stackelberg profit-driven model according to claim 1, characterized in that: The cloud service judges the accuracy, completeness, authenticity, and timeliness of medical data based on the following formula: The formula for calculating accuracy is: Where D anom It is an outlier; D All It is the total amount of all perceived medical data; The formula for calculating integrity is: Among them, D miss Indicates missing values ​​in medical data; The formula for calculating authenticity is: Where ε represents the quantified value of environmental factors, and satisfies 0≤ε≤1. This indicates the energy consumption of the IoMT device, and satisfies... The timeliness of medical data is determined when the MDR obtains the data, denoted as η. i And satisfying 1≥η1>η2>…>η k If the result is greater than 0, then the sum of the four attributes affecting QoD, x, can be obtained. i The calculation formula is: x i =Acc i +Comp i +Real i +η i 。

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