Biometrics-protected optical communication enabled by deep learning–enhanced triboelectric/photonic synergistic interface

• DOI: 10.1126/sciadv.abl9874
• Publication Date: 2022-01-19T18:59:26Z
• Authors: Bowei Dong; Zixuan Zhang; Qiongfeng Shi; Jingxuan Wei; Yiming Ma; Zian Xiao; Chengkuo Lee
• Keywords: Physical and Materials Sciences; 02 engineering and technology; 0210 nano-technology; 01 natural sciences; 0104 chemical sciences

Security is a prevailing concern in communication as conventional encryption methods are challenged by progressively powerful supercomputers. Here, we show that biometrics-protected optical communication can be constructed by synergizing triboelectric and nanophotonic technology. The synergy enables the loading of biometric information into the optical domain and the multiplexing of digital and biometric information at zero power consumption. The multiplexing process seals digital signals with a biometric envelope to avoid disrupting the original high-speed digital information and enhance the complexity of transmitted information. The system can perform demultiplexing, recover high-speed digital information, and implement deep learning to identify 15 users with around 95% accuracy, irrespective of biometric information data types (electrical, optical, or demultiplexed optical). Secure communication between users and the cloud is established after user identification for document exchange and smart home control. Through integrating triboelectric and photonics technology, our system provides a low-cost, easy-to-access, and ubiquitous solution for secure communication.