## 5 Results and Discussions
### Performance Evaluation  
The degree to which the cloud-based m-learning assisted in controlling the infrastructural and technological challenges is computed by using the student's capability to admit the data uploaded into the cloud. Figure 4 depicts that 90% that the data increased entry to the content and more than 60% of the students decided data access is easy. Students  
Figure 3: Workflow based on the encryption and decryption process. who identified the complexities in accessing the content recognized that these were due to poor network connection and the cost of the data for downloading and watching video. Students, who cannot be able to download the educator's data on their own, received the files from the classmates through Xender or Bluetooth. Whereas this describes the time for accessing the data, which took a long time for few students, the solution is to assure that all the participants accepted the data prior to class. The consequences of cloud computing-based m-learning on students learning experience are established by the two variables. The first variable is that asking students to compare the learning experiences before and after their commitment to m-learning. The second variable is with the help of comparing student attitudes to m-learning before and after the trial. Figure 5 depicts that about 90% of the students stated that m-learning prepared them faster and easier, whereas 73% of the students established it as useful. Figure 6 depicts the damaging effects of m-learning security threats to students. The most frequent consequences are confidential ratio loss, psychological damage, loss of study hours, performance loss and no effects. Of the students, 85.71% indicated the confidential ratio loss, 47.62% indicated psychological damage, 71.93% perceived loss of performance, and 3.53% perceived no effects. Figure 7 describes the security issues encountered when using mobile devices for m-learning. Most of the students agreed that theft is the concern when mobile devices are utilized for learning purposes, 67.18% of the students perceived theft of mobile device, 72.85% of the students responded that the malware attack is a major concern, 77.44% of the students indicated that their friends utilized their mobile device without their authorization, 35.24% of the students indicated the denial of service, and 3.82% indicated there were no security attacks. The encryption time and decryption time for the various file sizes in KB for the proposed method is tabulated in Table 2. From the evaluation results, the proposed encryption and decryption scheme obtains lesser time when compared with other encryption schemes. The table describes the time required for the encryption and decryption time for the ATS scheme. Figure 4: Consequences of cloud computing on m-learning. The time obtained for downloading and uploading is minimized, and it has low memory consumption. The time changed by altering the system configuration; thus, the average of the entire earlier work time was obtained as a reference. Table 3 demonstrates the downloading and uploading time for various file sizes. Figure 5: M-learning experience of the students. Figure 6: Damaging effects of m-learning security threats to students. Concerning the period for communication with the students in the lecture, students demand requesting questions that are listed on educator's screen; however, these questions are reacted due to the accessibility of time when the flow of the topic is completed. In the question time, students are provided access to allocate the data, text or file by the teacher. It is exposed to launch attacks by distributing malicious data from trustless students. Figure 8 describes the interaction of the average student's time per hour. The results describe that if 10 questions are asked, then the interaction of the student per hour is 13%, 20%, 26% and 32% for the average question number reacted as 2, 3, 4 and 5 questions in the existing method.