Secure Data Transactions in Mobile Cloud Computing using FAAS

Abstract

In recent times, security breaches have come to light in mobile cloud transactions, raising concerns about the vulnerability of data stored in mobile clouds. This data is at risk of tampering or unauthorized modification by external users, especially because it resides within a public cloud infrastructure managed by organizations. Such breaches can significantly impact the authenticity and integrity of the stored data. Mobile cloud computing (MCC) is a technology designed to facilitate the transfer of data and communication with end-users over the internet through a mobile cloud infrastructure. To address the urgent need to secure and protect data stored in mobile clouds, we propose the implementation of the Mobile Cloud-Security Model (MCSM). This innovative model is poised to provide an elevated level of data security and integrity for user data by harnessing the power of Federated Learning (FL) and Federation as a Service (FaaS). Federated Learning (FL) seamlessly integrates into the data training process, culminating in the generation of a model using the data hosted in the mobile cloud. This pioneering approach enables collaborative model training while steadfastly upholding data privacy and security. Federation as a Service (FaaS) represents a cloud-based solution that streamlines collaboration and data sharing among diverse organizations or entities. It simplifies the complex processes of configuring trust relationships, managing identities, and establishing data exchange agreements among federated entities, all made possible through the provision of Service Level Agreements (SLAs) for data stored in the mobile cloud. The user data stored in the mobile cloud will be retrieved using Machine Learning (ML) algorithms that learn from user data. Subsequently, this data is offloaded from the edge devices. The outcome of this research is to maintain user data within the FAAS cloud service with higher-level of confidentiality, security and integrity of user’s data.