Abstract
The utilization of mobile learning continues to rise and has attracted many organizations, university environments and institutions of higher education all over the world. The cloud storage system consists of several defense issues since data security and privacy have become known as the foremost apprehension for the users. Uploading and storing specific data in the cloud is familiar and widespread, but securing the data is a complicated task. This paper proposes a cloud-based mobile learning system using a hybrid optimal elliptic curve cryptography (HOECC) algorithm comprising public and private keys for data encryption. The proposed approach utilizes an adaptive tunicate slime-mold (ATS) algorithm to generate optimal key value. Thus, the data uploaded in the cloud system are secured with high authentication, data integrity and confidentiality. The study investigation employed a survey consisting of 50 students and the questionnaire was sent to all fifty students. In addition to this, for obtaining secure data transmission in the cloud, various performance measures, namely the encryption time, decryption time and uploading/downloading time were evaluated. The results reveal that the time of both encryption and decryption is less in ATF approach when compared with other techniques.
Highlights
In the past few years, breakthrough technological innovation and progression have brought forth another new approach to learn in university surroundings, named mobile learning or m-learning [1]
The mobile learning system is influenced directly by progressive technological advancements and the issues based on security and privacy are entirely different from the e-learning system
This paper proposes a cloud-based mobile learning system using a hybrid optimal elliptic curve cryptography (HOECC) algorithm comprising public and private keys for data encryption
Summary
In the past few years, breakthrough technological innovation and progression have brought forth another new approach to learn in university surroundings, named mobile learning or m-learning [1]. Mobile learning implements suitable service applications based on multimedia, containing various modes of operation and friendly human interfaces It accesses numerous resource networks using diverse network connection approaches [5]. Feature-based mobile learning is utilized in various educational activities and acts as a mediating tool to gather the educational materials and to learn the relevant topics using mobile devices via wireless technologies [10]. This paper proposes a cloud-based mobile learning system using a hybrid optimal elliptic curve cryptography (HOECC) algorithm comprising public and private keys for data encryption. Proposing hybrid optimal elliptic curve cryptography for data encryption, thereby generating the public and private keys; Proposing an adaptive tunicate slime-mold algorithm to select optimally the random value and to generate optimal keys; Comparing the proposed ATS approach with various other existing techniques to determine the system effectiveness.
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