## 6 Results and Discussion
### Performance Analysis Using CPA and CCA  
Comparison of performance analysis of the ABC-ROA-based privacy preservation system over the existing heuristic algorithms in terms of chosen ciphertext attacks (CCA) and chosen plaintext attacks (CPA) with three datasets is given in Tables 2 and 3, respectively. In CPA, the attacker can be used to encrypt the message. Hence, the goal of the CPA attack is to reduce the security of the encryption scheme. Here, symmetric and asymmetric cryptography can be used. However, the CPA is often feasible in the diverse applications. Since the CPA is essential for public key cryptography where the encryption key is public and so attackers can encrypt any plaintext they choose. Moreover, the CCA can able to decrypt the ciphertext message. Here, the CCA can be widely used in cryptanalysis to collect information by obtaining the decryptions of the chosen ciphertext, since it needs to recover the hidden secret key which is used for the decryption. The proposed model has more secure shared data in the transmission while analyzing the results. The CCA value of the developed system is guaranteed with a lower value on raising the proportion of key variations for all three datasets. From the dataset 2 analysis of CPA, the ABC-ROA-based privacy preservation model has high performance of 7.58%, 5.93%, 4.15%, and 7.64% than HHO, EF-HHO, BCO, and ROA for the key variations of 50. The proposed blockchain-based privacy preservation model is more effective than other heuristic algorithms.  
Figure 9: Performance analysis of the designed blockchain-based privacy preservation model concerning (**a**) dataset 1, (**b**) dataset 2, and (**c**) dataset 3.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Key Variations in the Percentage** & **HHO [29]** &
\begin{tabular}{c} **EF-HHO** \\ [30] \\ \end{tabular} & **BCO [27]** & **ROA [28]** & **ABC-ROA** \\ \hline \multicolumn{5}{c}{Dataset 1} \\ \hline
10 & 99.911 & 91.762 & 95.836 & 99.319 & 87.762 \\ \hline
20 & 99.877 & 93.113 & 96.495 & 99.396 & 89.113 \\ \hline
30 & 99.845 & 94.312 & 97.079 & 99.673 & 90.312 \\ \hline
40 & 99.873 & 95.739 & 97.806 & 99.787 & 91.739 \\ \hline
50 & 99.927 & 96.462 & 98.194 & 99.861 & 92.462 \\ \hline \multicolumn{5}{c}{Dataset 2} \\ \hline
10 & 99.909 & 91.626 & 95.767 & 99.31 & 87.626 \\ \hline
20 & 99.876 & 92.894 & 96.385 & 99.389 & 88.894 \\ \hline
30 & 99.843 & 94.071 & 96.957 & 99.669 & 90.071 \\ \hline
40 & 99.871 & 95.452 & 97.661 & 99.784 & 91.452 \\ \hline
50 & 99.926 & 96.283 & 98.105 & 99.859 & 92.283 \\ \hline \multicolumn{5}{c}{Dataset 3} \\ \hline
10 & 99.926 & 92.981 & 96.454 & 99.429 & 88.981 \\ \hline
20 & 99.899 & 93.969 & 96.934 & 99.494 & 89.969 \\ \hline
30 & 99.872 & 94.909 & 97.391 & 99.729 & 90.909 \\ \hline
40 & 99.895 & 96.057 & 97.976 & 99.823 & 92.057 \\ \hline
50 & 99.94 & 96.858 & 98.399 & 99.884 & 92.858 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Effectiveness analysis using CCA with three datasets for the developed blockchain-based data privacy preservation system over Ethereum network.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Key Variations in the Percentage** & **HHO [29]** &
\begin{tabular}{c} **EF-HHO** \\ \end{tabular} & **BCO [27]** & **ROA [28]** & **ABC-ROA** \\ \hline \multicolumn{5}{c}{Dataset 1} \\ \hline
10 & 58.784 & 52.465 & 55.624 & 58.236 & 43.465 \\ \hline
20 & 62.388 & 59.351 & 60.87 & 61.866 & 50.351 \\ \hline
30 & 65.623 & 63.651 & 64.637 & 65.13 & 54.651 \\ \hline
40 & 68.534 & 65.454 &