Applying Blockchain Technology and Facial Recognition to Unmanned Stores

In this study, we utilize blockchain to design an information transmission system for unmanned stores. It is aimed to create a network for exchanging information that does not rely on a third party, a so-called decentralized system. To achieve it, a peer-to-peer (P2P) network replaces the master–slave architecture and uses asymmetric encryption to identify the system users. To authenticate the identities of the stores' customers, we use the face recognition network FaceNet developed by Google. FaceNet has several advantages that make it suitable for performing identity authentication in an unmanned store, including its high accuracy and convenience. A database of face images is required to perform facial recognition, but to address privacy concerns, every pixel in all images in the database is encrypted using the Rivest-Sharmir-Adleman (RSA) algorithm. The system proposed in this paper has three identity endpoints: the host end, the recognition end, and the client end. Messages are transmitted through a P2P network, and a directed acyclic graph is used to achieve message broadcasting while avoiding infinite loops when sending and receiving messages. A sidechain is used to change the structure and consensus mechanism of a traditional blockchain so that they can apply to more scenarios, thereby increasing scalability. The simulation results are displayed via the user interface.