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Enhancing Legal Risk Management Through Advanced Multi-Feature Recognition Techniques

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  • Xiaoying Li

    (Henan Police College, China)

Abstract

Biological multi-characteristic identification technology utilizes individuals' innate and stable biometric information, offering higher security, efficiency, and convenience compared to traditional methods. However, as biometric data is sensitive personal information, its misuse may threaten property, information, and life safety. With the increasing application of this technology, incidents of infringement, forgery, and theft have risen. This paper analyzes the legal risks associated with its use, revealing technical flaws, environmental influences leading to recognition errors, insufficient legal frameworks, and weak self-regulation. Corresponding risk control measures are proposed, focusing on technical verification, legal support, industry regulation, and privacy awareness.

Suggested Citation

  • Xiaoying Li, 2025. "Enhancing Legal Risk Management Through Advanced Multi-Feature Recognition Techniques," International Journal of Knowledge Management (IJKM), IGI Global Scientific Publishing, vol. 21(1), pages 1-19, January.
    • Handle: RePEc:igg:jkm000:v:21:y:2025:i:1:p:1-19
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    References listed on IDEAS

    as
    1. Shenghui Zhou, 2024. "Gamifying language education: the impact of digital game-based learning on Chinese EFL learners," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    2. Stephen L. Chew & William J. Cerbin, 2021. "The cognitive challenges of effective teaching," The Journal of Economic Education, Taylor & Francis Journals, vol. 52(1), pages 17-40, January.
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