User Identity Recognition Based on Wireless Sensor Network and Internet Finance Development

Author:

Hua Tianxin1ORCID,Zhang Lingling1

Affiliation:

1. Jilin Normal University, Siping, Jilin 136000, China

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.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3