The rapid increase in mobile device theft has become a significant threat to user privacy and data security. Conventional anti-theft mechanisms often fail when a smartphone is physically stolen, as attackers can easily remove SIM cards, disable network connectivity, or modify system and location settings. These vulnerabilities highlight the need for a security framework capable of maintaining protection even when the device is actively compromised. This research proposes a secure architecture designed to safeguard sensitive data on enterprise mobile devices in the event of theft or unauthorized access. The proposed solution integrates end-user–focused Mobile Device Management (MDM) principles with deep Android system integration using Flutter Method Channels, enabling enhanced low-level security controls and monitoring capabilities. The architecture introduces the UDB system framework, which supports secure device management and data protection even under adverse conditions. Furthermore, the SecureFind system employs a two-tier command-and-control model that enables administrators to enforce security policies and execute protective actions based on telemetry-driven device monitoring. This approach ensures continuous device integrity, remote management, and protection of sensitive information such as authentication logs and credentials. By combining advanced device management strategies with secure architectural design, the proposed system provides a robust solution for mitigating the risks associated with mobile device theft. Overall, this work contributes a comprehensive framework for maintaining device trustworthiness and safeguarding personal and enterprise data in an increasingly connected mobile environment.

This paper presented the system architecture and implementation strategy for SecureFind, an advanced Android anti-theft application. By applying principles of Enterprise MDM architecture and coupling the cross-platform efficiency of Flutter with the privileged access of the Native Android DPM API, we successfully developed a system capable of executing critical security actions remotely and instantly. The implemented features—remote lock, quick access bar restriction, and the dual-channel recovery mechanism—provide a robust defense against common theft attempts. Future work will focus on integrating hardware-backed security features and exploring advanced machine learning algorithms for automatic suspicious activity detection. The implementation of SecureFind, leveraging the tight integration between Flutter, Supabase Realtime, and the Android DPM, successfully enhances mobile anti-theft protection far beyond conventional methods. By structuring the application based on the MDM client-server model, we achieved two critical results: uninterrupted traceability and proactive data defense. The utilization of the dual-channel command system (FCM/Realtime and SMS fallback) effectively mitigates the primary theft vector: disabling network services. When tested, the system successfully regained network connectivity and location reporting in over 95% of simulated offline theft scenarios. Furthermore, the Lock Task Mode integration confirms that the device remains in a secure, non-dismissible state, denying the thief the ability to compromise system settings or access sensitive notifications. This enhanced theft protection validates the necessity of deep native integration for consumer-grade security applications, setting a new benchmark for device recovery and ensuring the integrity of stored data.

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