# A Review of Blockchain-Based Secure Sharing of Healthcare Data
## 3 Blockchain in Healthcare Data
### Blockchain with IOMT  
The IOMT includes various medical devices that use computer networks to connect and detect parameters of patients' signs. IOMT brings great advantages for patients' disease management, and the detection of physical signs can detect diseases as soon as possible to seek medical treatment [30]. However, there are many IOMT products in the market without unified management standards, and it is prone to information leakage [31]. Blockchain brings a solution for the security of medical IOMT [32]. Figure 3 depicts the blockchain and IOMT. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Ref.** & **Blockchain Types** & **Storage Methods** & **Data Encryption** & **Access Control** \\ \hline
[23] & public & On-chain storage & no & coarse grained \\
[24] & public & Off-chain storage & yes & fine grained \\
[25] & private & On-chain storage & yes & coarse grained \\
[26] & hybrid & Off-chain storage & no & coarse grained \\
[27] & public & Off-chain storage & yes & coarse grained \\
[28] & public & Off-chain storage & no & fine grained \\
[29] & public & Off-chain storage & yes & fine grained \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of methods. [PERSON] et al. developed an IOMT-based data acquisition system in order to achieve secure storage and sharing of medical data [33]. The system can collect data from multiple medical devices simultaneously to achieve real-time collection of patient health records during surgery. The system is designed as a cloud server-based anonymous medical data sharing scheme with a proxy re-encryption algorithm. This approach improves the security of private medical data sharing. The system is implemented based on Hyperledger Fabric, a permissioned blockchain architecture, with a two-channel structure deployment architecture and medical chain code designed for data management and access control. The kafka consensus algorithm is used in this method. This consensus algorithm can tolerate the failure of half of the nodes, but it cannot tolerate malicious nodes. This makes the system more vulnerable to attacks. A novel blockchain-based secure authentication technology was proposed by [PERSON] to enhance the security of sensitive medical data transmitted between patients and hospitals [34]. Lamport Merkle Digital Signature (LMDS)  
Figure 3: Blockchain and IOMT. performs signature generation and verification here to enable secure transmission of sensitive medical data in cloud server-based medical IoT networks. Smart contracts enable transacting parties (i.e., patients and physicians) to set conditions and automate operations through the cloud server, reducing the work of third parties. Smart contracts also have different addresses and accounts on the blockchain so that each IoT device can view and execute its instructions, thus reducing communication overhead. [PERSON] et al. present a novel deep learning and blockchain-assisted secure image transmission and diagnosis model for IoMT [35]. The proposed model includes several processes, in particular, data collection, secure transactions, hash value encryption and data classification. In the primary stage, patient details are collected using IoT tools and then encrypted using the GO-FFO algorithm. In addition, the hashes in the blockchain are encrypted and compressed by NIS-BWT technology. Finally, the classification process is performed using the DBN model. The improved encryption algorithm, although more secure, takes longer to encrypt and decrypt than other algorithms. An API interface is provided in the system proposed by [PERSON] [36]. This interface generates and maintains health data between the healthcare provider and the patient. In addition, smart contracts are fully used in the proposed system to prevent malicious behavior by setting secure rules through smart contracts. The method uses only simple authentication. If fine-grained properties can be given to the nodes. This could make the model more perfect. [PERSON] et al.