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

Author:

Dong Bowei123ORCID,Zhang Zixuan12ORCID,Shi Qiongfeng12ORCID,Wei Jingxuan12ORCID,Ma Yiming12ORCID,Xiao Zian12ORCID,Lee Chengkuo123ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore 117583.

2. Center for Intelligent Sensors and MEMS, National University of Singapore, Singapore, Singapore 117608.

3. NUS Graduate School—Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore 119077.

Abstract

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.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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