###### Abstract
The results explain that the average number of attributes authority should be less than 10 in order to achieve the optimum computational cost. In Figure 9, we have compared our proposed access control policies for accessing the personal health records. These access control policies are updating, authentication, authorization and search policies. We have used the attributes such as confirmation time and number of policies. From the simulations its very obvious that authorization takes less time as compared to other policies hence it justified that our proposed access control algorithm is more secure and cost effective as compared to the benchmark models such as Medrec and Medchan. In Figure 10, we plot the results of our experimental evaluations based on the proposed access control policies. We have categorized the access control policies. These policies are the read, write, delete, update and revoke policies. We have compared each policy with the execution time. From the simulation results, it is clear that the our proposed access control policies take less time as compared to the benchmark models. Table 2 explains the comparative analysis of our proposed framework and the benchmark models. From Table 2 it is very clear that our proposed framework is more efficient in the case of security, privacy and by providing access control to the users in order to access their data securely. For Cross-domain based access control using multiple CA we have conducted experiments, and plotted results in Figure 11. We considered different domain ranges from 0 to 400. From the simulation results in Figure 11, it is evident that our proposed framework is best up-to the 70 cross domain, respectively. In Figure 12, we have provided the simulation results based on the number of access control policies. These access control policies are used for authorization, authentication and update policies. Our main approach is authorization, which is more concern about security. From Figure 12, it is obvious that our proposed access authorization method takes much less time as compared to other policies. Hence, our proposed method is more secure and efficient as compared to other policies. Figure 8: Analysis of deployment confirmation time. Figure 10: Comparative Analysis of proposed flexible Access Control policies based on number of Attributes Authority K = 1 with the benchmark models. Figure 9: Analysis of Access Control Policies based on the number of attributes and certificate authority. Figure 15 shows the detailed information about the number of group of policies and the EHR sent per second. The x-axis denotes the group of access control policies, while the y-axis shows the EHR, which is sent per second. We did comparative analysis with our proposed framework and benchmark model, that is, medrec based on number of transactions for the same number of policies. It is evident from the graph that the proposed framework surpasses medrec for the same policies. In Figure 16, the comparison is carried out on the basis of number of nodes and response time. From Figure 16, it is clear that the greater the response time, the less efficient the model for the same number of nodes will be. It is evident from Figure 16 that our proposed framework takes less response time in  
Figure 12: Comparative Analysis of proposed flexible Access Control policies based on number of Attributes Authority K = 1 with the benchmark models. Figure 13: Evaluation results of number of evaluations vs. confirmation time. order to transfer the electronic health records. We carried out the experiment for the same number of nodes hence our technique response in a very short time as compared to the benchmark model, which takes more time. The main reason for our technique is that we are using stream based data whereas the benchmark models have used block data. In order to check the integrity of packets, only the last bit of the stream is required to check for the integrity. Hence, for \(n\) bit of stream the complexity will be equal to \(b-1\).