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Physical Unclonable Function (PUF)-Based e-Cash Transaction Protocol (PUF-Cash)

机译:物理不可渗透功能(PUF)基于电子现金交易协议(PUF-CAB)

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Electronic money (e-money or e-Cash) is the digital representation of physical banknotes augmented by added use cases of online and remote payments. This paper presents a novel, anonymous e-money transaction protocol, built based on physical unclonable functions (PUFs), titled PUF-Cash. PUF-Cash preserves user anonymity while enabling both offline and online transaction capability. The PUF’s privacy-preserving property is leveraged to create blinded tokens for transaction anonymity while its hardware-based challenge–response pair authentication scheme provides a secure solution that is impervious to typical protocol attacks. The scheme is inspired from Chaum’s Digicash work in the 1980s and subsequent improvements. Unlike Chaum’s scheme, which relies on Rivest, Shamir and Adlemans’s (RSA’s) multiplicative homomorphic property to provide anonymity, the anonymity scheme proposed in this paper leverages the random and unique statistical properties of synthesized integrated circuits. PUF-Cash is implemented and demonstrated using a set of Xilinx Zynq Field Programmable Gate Arrays (FPGAs). Experimental results suggest that the hardware footprint of the solution is small, and the transaction rate is suitable for large-scale applications. An in-depth security analysis suggests that the solution possesses excellent statistical qualities in the generated authentication and encryption keys, and it is robust against a variety of attack vectors including model-building, impersonation, and side-channel variants.
机译:电子货币(电子货币或电子现金)是通过在线和远程付款的添加使用案例增强的物理钞票的数字代表。本文介绍了一种基于物理不可分类的功能(PUF)的新颖,匿名电子货币交易协议,标题为PUF-Cash。 PUF-Cash保留用户匿名,同时启用离线和在线事务功能。 PUF’ S的隐私保留属性被利用,以在基于硬件的挑战和ndash中创建交易匿名的蒙蔽代币;响应对身份验证方案提供了一种不透明的典型协议攻击的安全解决方案。该方案受到了杂交&rsquo的启发,在20世纪80年代和随后的改进。与Chaum&Rsquo的计划不同,它依赖于RIVEST,Shamir和Adlemans&Rsquo; S(RSA’ S)乘法均匀性,本文提出的匿名方案利用了合成的集成电路的随机和独特的统计特性。使用一组Xilinx Zynq字段可编程门阵列(FPGA)实施和演示PUF-Cash。实验结果表明解决方案的硬件占地面积很小,交易率适用于大型应用。深入安全分析表明,该解决方案具有所生成的认证和加密密钥的优异统计质量,并且对各种攻击向量具有稳健,包括模型建设,模拟和侧通道变体。

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