Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 40 | Offline Multi-Factor Authentication Smart Safe |
Ruichao Chen Ziheng Yu Ziyuan Luo |
design_document1.pdf final_paper1.pdf final_paper2.pdf final_paper3.pdf proposal1.pdf |
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| Project Name: Offline Multi-Factor Authentication Smart Safe Overview Traditional single-point authentication safes are vulnerable to key theft or password cracking. Our project is a standalone, battery-powered smart safe equipped with a three-in-one multi-factor authentication (MFA) system: edge AI facial recognition, fingerprint recognition, and RFID. This system is designed for secure and intuitive interaction, verifying biometric data locally and triggering the physical electromechanical lock instantly, without relying on vulnerable cloud networks or smartphone apps. Unique Features Unlike commercial smart locks that process data via Wi-Fi (which poses significant privacy and cybersecurity risks), our system performs all biometric matching entirely at the edge. Crucially, the system architecture is controlled by a strictly non-blocking finite state machine (FSM). This FSM logic supports a “high-security mode” (enforcing strict sequential multi-factor authentication), resisting brute-force attacks. These features are typically found in enterprise-grade security systems, not consumer-grade desktop safes. Brief Technical Overview The core component is a custom-designed PCB employing a dual-MCU architecture: an ESP32-S3 (or other hardware) handles the DVP camera interface and edge AI algorithms, while an STM32 manages the FSM and peripheral polling. The main challenge in the hardware design lay in building a robust power distribution network and high-current MOSFET drive circuitry. This ensured that the 12V electromechanical electromagnetic lock could safely withstand peak transient currents without causing voltage drops to sensitive logic circuitry. |
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