Abstract
Wireless sensor network is a multisensor wireless network system, which consists of multiple sensors and is configured independently. Because the network generates a large amount of data, the frequency, performance, and computing power of sensor nodes are limited, and they are particularly vulnerable to harsh environments and malicious attackers. This leads to the occurrence of malicious nodes, emergencies, and abnormal data in the sensor network system. Failures can also have a significant impact on sensor network services. The two main functions of wireless sensor network security are abnormal node detection and data anomaly detection. These two directions are mutually independent and complementary. Therefore, under the promotion of the rural revitalization strategy and the precision poverty alleviation strategy, China has increased its agricultural efforts. At this stage, all localities focus on the construction of rural financial systems to ensure that scattered farmers and rural small and micro-enterprises receive comprehensive financial services. The establishment of a rural financial system based on “intelligent forecasting” can improve financial development theories and build new ideas for rural financial development. And, the balance between realization and profitability, and then, through the use of Internet technology to make traditional financial institutions more effective in providing financial services, new online financial platforms can use them to make up for the existing shortcomings of traditional financial institutions as much as possible. In this article, through the research on the intelligent prediction of sensor data anomaly detection, it is applied to the development of rural finance and promotes the development of rural finance.
Highlights
In recent years, with the rapid development of computer technology, electronic equipment, wireless networks, and communication systems, wireless sensor networks have continued to emerge and have gradually become an important channel for people to obtain data and information [1]
After screening and removing malicious nodes in the sensor network, a fault detection method based on a distributed multilayer wireless sensor network is introduced [8]. rough the analysis of false datasets and real-time environmental data collection data, it is shown that compared with the central system and the reference system, the improved anomaly detection program can achieve a higher detection rate, false alarm rate, and lower communication utilization [9]
Using the concepts and theories related to the overview, firstly, it analyzes the status quo of rural financial development under the background of “Internet + intelligent forecasting” from the service functions of traditional rural financial institutions and the service functions of Internet rural financial institutions; Alibaba and CreditEase analyze and demonstrate the three typical rural finance “Internet + smart forecasting” cases to obtain development information: clarify the “Internet + smart forecasting” agricultural development strategic goals, make full use of big data, and promote the self-improvement of local financial institutions; By further analyzing the problems existing in the development of rural finance in the context of the “Internet,” we found that there are various problems in rural financial risks
Summary
With the rapid development of computer technology, electronic equipment, wireless networks, and communication systems, wireless sensor networks have continued to emerge and have gradually become an important channel for people to obtain data and information [1]. Wireless sensor networks have the characteristics of limited node sources and are easy to break [2] Technologies such as mandatory passwords and secure routing have improved the security of sensor networks, there is still a lack of effective methods to detect abnormal information in the sensor network, making the sensor network more effective. E improvement of data anomaly detection technology can greatly promote the future application and development of sensor networks. 2. Related Works e literature introduces the application background of wireless sensor networks, describes the research background and practical significance of malicious nodes and abnormal data detection, analyzes the current status of the investigation of malicious messages and abnormal information detection technologies at home and abroad, and provides a complete, structured, and summarized summary [13]. E literature introduces an abnormal data detection method for distributed wireless sensor networks based on hierarchical aggregation [15]. Design and Implementation of the Intelligent Prediction Method Based on Abnormal Detection of Sensor Data
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