## 5 Simulation Results and Discussion  
In this section, the experiments are conducted for performance evaluation. The proposed scheme is implemented on the Java platform, in an Intel core with 2 GB RAM. The computation cost of encryption and decryption is computed. All of these systems not only provide data security, but also accomplish the access control of encrypted data on a cloud network. While comparing the data collaboration schemes of ABE [27] and HABE [30], the proposed BH-WABE attains partial signing, and full delegation, with less workload (data user and WAA) and also accomplishes lightweight key management in a large-scale consumer.  
In the proposed scheme, various input files of different sizes (in kB) are encrypted and decrypted by blowfish algorithm. Key generation and weight generation are also done by blowfish algorithm. This algorithm is generated for security purpose and also it yields less execution timings for \"encryption and decryption process\". The security aspect of blowfish encryption approach has been enhanced. The final outcome of the proposed scheme is illustrated in Table 1. The time taken for encryption and decryption process by the proposed BH-WABE is compared with the conventional HABE scheme by considering the performance metrics.  
**Encryption time**: The time taken to encrypt the data is termed as encryption time. It is used to estimate the throughput of an encryption approach as well as to evaluate the speed of the system. The encryption time can be determined by defining the time taken to generate a ciphertext from a plaintext and it is graphically represented in Figure 5.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Input Data** & **File Size (GB)** & **Encryption Time (s)** & **Decryption Time (s)** & **Throughput** \\ \hline \(l_{1}\) & 1 & 118 & 113 & 0.00847 \\ \(l_{2}\) & 2 & 230 & 221 & 0.00869 \\ \(l_{3}\) & 3 & 341 & 598 & 0.00874 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Experimental results of execution time of encryption/decryption, throughput for BH-WABE.  
Figure 4: Data user side (decryption process).  
**Decryption time**: The inverse process of encryption process is termed as decryption process. However, the decryption time is defined as the time that a decryption algorithm takes to yield a plaintext from a ciphertext. The decryption time for the conventional HABE and the proposed BH-WABE is analyzed in Figure 6.  
**Throughput**: The ratio of the encrypted data file to the encryption time is referred as throughput. In Figure 7 it is seen that the throughput estimated from the proposed BH-WABE scheme is high when compared to the conventional HABE scheme.  
\[\text{Throughput}\ =\ \frac{\text{File size }(\text{kB})}{\text{Encryption time}} \tag{1}\]  
Figure 5: Computation time of encryption. HABE: hierarchical attribute-based encryption.  
Figure 6: Computation cost of decryption.  
**Cost of secret key analysis:** The computation cost and storage overhead of secret key are analyzed as plotted in Figure 8. The \(y\)-axis denotes storage overhead or time cost of a user's secret key. The \(x\)-axis denotes the number of weighted attributes in a user's secret key.  
**Cost of ciphertext analysis:** The storage overhead and computation cost of encrypting data by a data owner are compared as plotted in Figure 9. The \(y\)-axis denotes storage overhead or time cost of encrypting data by the data owner. The \(x\)-axis denotes the number of weighted attributes in access policy defined by the data owner.  
Figure 8: Cost of user secret key generation. (**a**) Time cost analysis; (**b**) Storage cost analysis.  
Figure 7: Comparison on throughput of HABE and BH-WABE.