论文标题
保密，隐私和存储的嵌套卷积卷积代码
Nested Tailbiting Convolutional Codes for Secrecy, Privacy, and Storage
论文作者
论文摘要
考虑到具有生物识别或物理标识符的关键协议问题，关键注册的终端以及重建终端。提出了嵌套的卷积代码设计，该设计在重建过程中执行载体量化和误差控制过程中执行矢量量化。物理标识符具有小误差概率说明了设计的收益。嵌套卷积代码的一种变体在最著名的钥匙率和存储率比上有所改善，但具有很高的复杂性。第二个具有较低复杂性的变体的性能类似于嵌套的极性代码。结果表明，与标识符的密钥一致性代码的选择主要取决于复杂性约束。
A key agreement problem is considered that has a biometric or physical identifier, a terminal for key enrollment, and a terminal for reconstruction. A nested convolutional code design is proposed that performs vector quantization during enrollment and error control during reconstruction. Physical identifiers with small bit error probability illustrate the gains of the design. One variant of the nested convolutional codes improves on the best known key vs. storage rate ratio but it has high complexity. A second variant with lower complexity performs similar to nested polar codes. The results suggest that the choice of code for key agreement with identifiers depends primarily on the complexity constraint.
