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    此摘要是机器生成的。

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    科学领域:

    • 生物识别信息 生物识别信息
    • 信号处理 信号处理
    • 网络安全 网络安全

    背景情况:

    • 生物识别为记住凭证提供了一个替代方案.
    • 心电图 (ECG) 生物识别显示出潜力,但由于模板保护薄弱,面临隐私和安全挑战.
    • 现有的ECG生物识别系统难以保护敏感的用户数据.

    研究的目的:

    • 引入基于Bloom波器的新策略,从心电图数据中生成安全的生物识别模板.
    • 在基于ECG的识别和验证系统中增强隐私和安全.
    • 提高ECG生物识别系统对未经授权的访问和变化的稳定性.

    主要方法:

    • 开发基于Bloom镜的模板生成技术,用于ECG生物识别.
    • 整合非线性转换以防止模板重建.
    • 实施基于四分位数范围的方法来确认身份.
    • 在识别和验证模式下对拟议方案的评估.

    主要成果:

    • 拟议的Bloom过器策略有效地解决了隐私和安全问题.
    • 非线性转换显著复杂化模板重建.
    • 四分区间范围方法提高了对变化和攻击的准确性.
    • 实现的平均等错误率为7.9% (识别) 和1.3% (验证).

    结论:

    • 基于Bloom波器的ECG生物识别模板生成提供了一个安全有效的解决方案.
    • 拟议的方法增强了用户隐私和系统安全.
    • 该系统在现实场景中表现出高精度和稳定性.