The amazing rise of digital currency is not only favored by investors but also attractive to lawbreakers for its anonymity and decentralization. This paper mainly discusses the intelligent digital currency and dynamic coding service system based on Internet of Things technology. In this paper, the RDCAR algorithm is used to realize the routing discovery process of the wireless network. When the intermediate node receives the RREQ message, first of all, to avoid the loop, it checks whether the same RREQ message has been introduced. If it has received it, it will discard it. Otherwise, it will cache the message and attach its own neighbor node list to the signal-to-noise ratio of the channel link, update the RREQ message, and broadcast it. The payment cipher is managed by the bank. When the user opens an account, the bank registers and sends it to the user. The key is generated by the algorithm chip, and the public key is kept in the bank background server. When the bill is delivered to the bank, the bank inputs all the elements on the bill on the counter terminal and transmits it to the verification machine for verification through the bank network. If the verification is correct, it indicates that the bill is indeed issued by the customer, and all bill elements are correct, and payment can be made. The node operation protocol of public chain and alliance chain maintains the operation of the Internet of Things system. The nodes of alliance chain generate new blocks according to the interval of 30 s. When the node fails to complete the block generation within 30 s, it will rotate to the next node. The mkfile command is used to generate 16b, 1 KB, 1 MB, and 1 GB files as input. The peak speed of the encoding service system is about 370 mb/s. The results show that the system designed in this study is robust and suitable for complex trading environment.
The process of global integration has accelerated, and the international financial market has become increasingly closely linked. The financial risks that come with them are becoming more complex and difficult to guard against. Multimedia modeling in Health Cloud biometric authentication and data management systems can be applied to the analysis of financial markets. Most of the current financial risk analysis models are based on a single time, and the models are relatively simple and cannot adapt to the current complex multidimensional mixed financial risk environment. Therefore, this paper aimed to analyze the spatial spillover effect of financial risk contagion based on the directed asymmetric (DAI) spatial econometric model. This paper proposed to transfer entropy information weight information and introduce the GARCH (generalized auto-regressive conditional heteroskedasticity) model to improve the traditional econometric model. By constructing a DAI measurement model, the spatial contagion of multidimensional mixed financial risks was analyzed, and on this basis, a generalized multidimensional economic space was established to analyze spatial spillover effects and analyze the specific path of spatial spillover effects. The model results in this paper showed that the degree of correlation between the stock and bond market varied greatly between countries. Among them, the change coefficient W s ⟶ b r s D of the event period was judged to have a large degree of negative change in the United Kingdom, Germany, and France in the European Union, which were −0.9885, −0.9876, and −0.9748, respectively. This showed that the model in this paper had a good and reliable ability to cope with the current multidimensional mixed complex financial risk environment and could be used as a reference for financial risk-related research. At the same time, it also proved that multimedia modeling in health cloud biometric authentication and data management system could provide a role in financial risk contagion analysis.
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