# HAE: A Hybrid Cryptographic Algorithm for Blockchain Medical Scenario Applications
## 4 Experiments and Analysis
### Experimental Analysis
#### 4.4.3 Analysis of Resource Consumption  
From an algorithmic perspective, as depicted in Figure 10, the CPU utilization for the hybrid cryptographic algorithm HAE exhibits a slight increase with the growth in data size. Nevertheless, this uptick remains modest, hovering between 20% and 30%. Furthermore, the HAE algorithm demonstrates a reduced CPU utilization rate for equivalent data sizes, compared to both the ECC and the combined AES+RSA algorithms. This suggests that HAE is more efficient in terms of resource consumption.  
Considering its practical application within blockchain medical contexts, as illustrated in Figure 5, medical data are encrypted and housed within the InterPlanetary File System (IPFS). The address hash returned by IPFS is then disseminated and stored across blockchain nodes. Given the minimal data volume within this hash, there is no significant resource consumption. As a result, the hybrid cryptographic algorithm HAE holds promising potential for deployment in blockchain medical scenarios.  
Table 5 presents a performance comparison among the HAE, ECC, and AES+RSA algorithms. As evident from the table, both HAE and ECC exhibit robust security levels. However, the inherent limitations of RSA render the AES+RSA combination slightly less secure than its counterparts. In terms of operational speed, HAE emerges as the fastest, followed by AES+RSA, with ECC trailing behind. Regarding resource consumption, HAE is the most efficient, while ECC consumes the most resources, and AES+RSA falls in between. In the broader context of blockchain healthcare applications, HAE's advantages become even more pronounced. Consider the use case illustrated in Figure 5: medical  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Breaking Time/Mips-YEARS** & **ECC/Bit** & **RSA/Bit** \\ \hline \(10^{4}\) & 132 & 768 \\ \(10^{12}\) & 160 & 1024 \\ \(10^{20}\) & 210 & 2048 \\ \(10^{31}\) & 283 & 3072 \\ \(10^{52}\) & 410 & 7680 \\ \(10^{67}\) & 571 & 15,360 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Key lengths of ECC and RSA with equal security.  
Figure 10: Comparison of CPU utilization of three cryptographic algorithms.  
data generated by Hospital 1 must be encrypted securely for storage, yet remain accessible for decryption by other entities, such as Hospital n, in a swift and efficient manner. Here, HAE's prowess is unparalleled. Firstly, from a security perspective, HAE employs AES for data encryption and uses ECC for the AES key encryption, effectively offering dual-layer protection for both data and key. Given the widespread validation of ECC and AES as secure algorithms, the integrity of medical data remains uncompromised. Secondly, in terms of time efficiency, HAE consistently outperforms both ECC and AES+RSA in encryption and decryption tasks, especially when handling equivalent data sizes. This implies that when entities like Hospital n retrieve and decrypt medical data from IPFS, HAE facilitates faster access to the original data. Lastly, concerning resource consumption, HAE is more resource-efficient than both ECC and AES+RSA. This efficiency is crucial in resource-sensitive healthcare environments, ensuring that encryption and decryption processes remain streamlined without straining the system. Furthermore, HAE's compatibility with IPFS is noteworthy. IPFS's content-based addressing mechanism allows for the segmentation and storage of large files. When paired with HAE's efficient encryption and decryption capabilities, a secure and efficient storage and retrieval solution for healthcare data is realized. In summation, the HAE hybrid cryptographic algorithm stands out in terms of security, time efficiency, and resource consumption, positioning it as a prime choice for the encryption, storage, and sharing of medical data in blockchain healthcare scenarios.