Enhancing Mobile Data Security with Zero-Trust Architecture and Federated Learning: A Comprehensive Approach to Prevent Data Leakage on Smart Terminals
DOI:
https://doi.org/10.70589/JRTCSE.2023.1.8Keywords:
Zero-Trust Architecture, Federated Learning, Mobile Data Security, Data Leakage Prevention, Virtual Remote Desktop, Thin Clients, Mobile Terminals, Privacy-Preserving Security, Dynamic Access Control, Secure Data TransmissionAbstract
The extension of critical enterprise data to mobile terminal devices has introduced a new challenge: data leakage on mobile devices. To address this issue, a Zero-Trust Architecture (ZTA) combined with Federated Learning (FL) for Mobile Data Security is proposed. This approaches users and implicit trust, enforces continuous verification of devices and users, and enhances mobile data security through privacy-preserving collaborative learning. It overcomes the limitations of traditional security methods, which often rely on static application-layer protection, by providing dynamic, multi-layered security. Additionally, by integrating the concept of thin clients with data leakage prevention for mobile terminals, a virtual remote desktop technology tailored to mobile devices is designed. This solution minimizes the risks associated with data stream transmission and ensures secure and efficient data access for mobile users. Based on these advancements, a comprehensive data leakage prevention system for mobile smart terminals has been designed and implemented, combining ZTA principles, federated learning, and advanced virtualization techniques to achieve robust and scalable security.
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Copyright (c) 2023 Mounica Yenugula, Akhila Reddy Yadulla, Bhargavi Konda, Santosh Reddy Addul, Vinay Kumar Kasula (Author)

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