Abstract
With the rapid development of computer network technology, the concept of “Internet +” has become more and more popular in recent years. The combination of the Internet and finance has particularly attracted people's attention, and the operating modes of many industries have also changed. Since the use of Internet technology can achieve data sharing and information exchange, the “Internet + Finance” model has broken the barriers of information asymmetry in the financial sector in the past and has made great contributions to China's multiple improvements. The financial market is very important to China's economic development. The identification of the ID function of the wireless sensor network is susceptible to interference and the identification accuracy is reduced. We propose an adaptive identification feature recognition algorithm based on an improved minimum gray tree. After calculating the similarity, the nearest neighbor matching algorithm is directly used to obtain the minimum matching cost corresponding to the wireless sensor network registration that is regarded as the recognized identity so as to realize the identity function adaptive recognition. In this regard, the simulation results show that the proposed algorithm has high recognition accuracy. With the pace of financial innovation, financial institutions have achieved rapid development on the basis of Internet service platforms. At the same time, as the core of preventing money laundering activities, financial institutions are also facing many issues in identifying “customers” in their work. This article analyzes the main content, implementation effects, and difficulty of customer identification in financial institutions and proposes relevant improvement plans.
Highlights
With the rapid development of information globalization in today’s society, the digitization and ambiguity of user ID caused by the Internet will lead to serious disclosure of personal information, which will undoubtedly bring new challenges to identification and technology. e security authentication methods currently in use include combined authentication of user names and passwords, authentication of special authentication objects, and so on [2]. ese authentication methods are easy to be stolen or imitated due to excessive human factors in the authentication process and cannot achieve high-level and high-precision security prevention and control [3]
Based on wireless sensor networks, this paper studies the development of user identification and network finance. is paper studies the characteristics of wireless sensor data, better data reduction, and data classification algorithms and proposes a basic action recognition method based on wireless sensor data
Aiming to improve the shortcomings of traditional identification algorithms, an adaptive identification algorithm based on the improved minimum gray tree of the visual sensor network is proposed. e simulation results show that the algorithm shows a high accuracy of identification
Summary
The recognition based on the characteristics of the action requires high-precision recognition of the action. Because it is difficult to change the user’s biometric characteristics, it is more difficult to imitate, so the possibility of theft is very small It is widely used in government, military, banks, welfare companies, social security bureaus, e-commerce, and Computational Intelligence and Neuroscience other fields [5]. E Internet finance model has been favored and valued by more and more users and enterprises for its advantages of high efficiency, low threshold, convenience, and low cost [6]. Summarizing the previous literature discussion and empirical research, we propose specific targeted antifraud prevention and control countermeasures for Internet financial platform users from the three directions of improving the level of Internet financial supervision, using financial technology to combat fraud, and building industry moral order [8]. Internet platforms provide prevention and control suggestions to reduce company losses and provide more ideas and methods for Internet financial platforms to combat fraud [9]
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