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Role-Based Identity01:21

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Role-based identities are central to understanding how individuals navigate social environments by adopting distinct self-conceptions aligned with various societal roles. These identities are not fixed traits but are constructed through personal actions and the social feedback individuals receive in context-specific interactions. Each social role, such as student, teacher, or friend, carries a set of expectations and norms that influence how people think, feel, and behave within that...
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User Identity Recognition Based on Wireless Sensor Network and Internet Finance Development.

Tianxin Hua1, Lingling Zhang1

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

Computational Intelligence and Neuroscience
|March 10, 2022
PubMed
Summary
This summary is machine-generated.

Internet+Finance enhances China's economy by breaking information asymmetry. A new adaptive algorithm improves wireless sensor network identity recognition accuracy, crucial for financial customer identification and preventing money laundering.

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Area of Science:

  • Computer Science
  • Financial Technology
  • Cybersecurity

Background:

  • The integration of Internet technology with finance, termed "Internet+Finance," has revolutionized industries by enabling data sharing and information exchange.
  • This model addresses historical information asymmetry in the financial sector, significantly contributing to China's economic improvements.
  • Financial institutions, vital for economic development, face challenges in customer identification, particularly in preventing money laundering activities.

Purpose of the Study:

  • To propose an adaptive identification feature recognition algorithm for wireless sensor networks (WSNs) to enhance recognition accuracy.
  • To analyze the challenges and propose improvements for customer identification in financial institutions, a critical aspect of anti-money laundering efforts.

Main Methods:

  • An improved minimum gray tree algorithm is developed for adaptive identification feature recognition in WSNs.
  • Nearest neighbor matching algorithm is employed to determine the minimum matching cost for WSN registration, enabling identity recognition.
  • Analysis of customer identification content, implementation effects, and difficulties within financial institutions.

Main Results:

  • The proposed adaptive algorithm demonstrates high recognition accuracy in simulations for WSN identity function.
  • Financial institutions leveraging Internet service platforms show rapid development.
  • Customer identification remains a complex issue for financial institutions, necessitating improvement plans.

Conclusions:

  • The developed algorithm offers a robust solution for accurate WSN identity recognition.
  • Addressing customer identification challenges is crucial for financial institutions to effectively combat money laundering.
  • The "Internet+Finance" model presents opportunities and challenges for financial sector development and security.