Abstract
Internet of Things finance is a new type of financial industry in which Internet of Things enterprises and financial institutions borrow information and communication technology and Internet of Things technology and use algorithms and models to realize payment, positioning, investment, measurement, capital financing, asset management, and information intermediary services. The purpose of this paper is to implement risk management and control based on the Internet of Things by enumerating, comprehending, and all-embracing data, effectively improve reliability and efficiency, and minimize risks under certain conditions. First this article on the Internet of things and Internet of things played a role in financial giving relevant summary and interpretation of the analysis of the present condition, and the rate of financial security and risk is based on Internet environment, and for financial security and risk measurement, positioning and computing scheme, attached to the unit and multiple positioning and Taylor calculation model, is used to determine and control the financial risk. In addition, beBS-T encryption model is used to encrypt financial nodes to strengthen financial security and reduce financial risks. AHP is then used to establish a risk judgment matrix to evaluate the financial system and calculate the index of risk weight. After that, simulation algorithm is used to check nodes and risk measurement experiments. The improved ant colony algorithm NACO is compared with the basic algorithm TACO, and the further improved TSN metric algorithm with increment is proposed. The conclusion is drawn as follows: The improved ant colony algorithm NACO is 23.46% lower than the basic ant colony algorithm TACO in the failure jitter end of risk measurement, while the incremental I-NACO algorithm shows better utility and is 7.1% lower than the NACO algorithm in the delay jitter of risk measurement. The Internet of Things is taking a deep role in the financial field, and its shape is in the making. In the process of controlling financial risks, it can make a great contribution to gradually innovate financial forms and reform business models.
Highlights
Prevention technologies can be added through positioning monitoring, encryption algorithms, node identification, risk measurement, and other methods to improve the security of IoT
It can be clearly seen from the table that the performance of the improved ant colony algorithm NACO is better than the basic ant colony algorithm TACO. en we show the effect of different network topologies in the experiment and observe Table 4 to see
The optimal solution of the NACO algorithm is better than the TACO algorithm. erefore, when financial risk measurement is based on the Internet of ings, the NACO algorithm can be preferred [21]
Summary
Main purpose of this article is to study, based on Internet environment, interpretation of the analysis of financial safety and risk, under the Internet of various methods of the docking financial effect and function, and for financial security and risk measurement, such as orientation, Taylor BEBS structuring model, T encryption method, AHP analytic hierarchy process (AHP) risk judgment matrix, evaluation of the financial system, calculate the risk weighting of the indicators and simulate the algorithm degree check node and risk measurement experiment, compare the improved ant colony algorithm NACO and the basic algorithm TACO, further put forward the improved algorithm with increment TSN measurement, through method calculation, experimental analysis, detection data, and verify its feasibility, in financial security and risk which can bring targeted optimization
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