Chapter 8 A Secured Framework for Cloud Computing Sana M. Bagban and H. A. Tirmare 1 Introduction Smartphones, provide wider range of applications such as image processing, files with different extensions, speech recognition, and many more. The demands for application and smartphone with such resources are increasing. Mobile cloud com- puting is a new concept that integrates cloud and mobile device to extend battery life and increase the performance of an application. The framework is used to design one or more constrained, such as energy consumption, CPU utilization, execution time and memory storage. AES technique is used for encrypting data for security purposes. The cloud computing consists of different deployment techniques that is: Private, public and hybrid cloud. The framework on leveraging energy efficiency focuses on service on cloud datacenters on the minimal instance of computation at runtime. In computational offloading, the main ideas are to migrate computational tasks from mobile to server in order to save energy on the mobile device. The main aims of the offloading decision we need to monitor the usage of network and band- width. For transferring data we require high bandwidth and network connectivity, where the system consists of wireless connection. It requires 4G, 3G or Wi-Fi con- nection for transferring data. Offloading refers to technique or terms of memory and computation. To login to the cloud and get the benefit of the access we have to pro- vide security by signing up with the Gmail account of user and notification and the link is sent for verifying and allowing access to use the cloud. Different modules and architecture systems have been proposed. S. M. Bagban (B ) · H. A. Tirmare Computer Science and Technology, Department of Technology, Shivaji University, Kolhapur, Maharashtra, India e-mail: sana.bagban8@gmail.com H. A. Tirmare e-mail: hat_tech@unishivaji.ac.in © Springer Nature Singapore Pte Ltd. 2020 V. K. Gunjan et al. (eds.), Cybernetics, Cognition and Machine Learning Applications, Algorithms for Intelligent Systems, https://doi.org/10.1007/978-981-15-1632-0_8 73