TC: Medium: From Statistics to Circuits: Foundations for Future On-chip Fingerprints

在一个每个人和每件事都通过电子方式连接的世界里，身份对于支持可信的交易至关重要。本项目研究设计和实现片上指纹的新技术。这样的指纹建立了电子系统的硬件身份。芯片上的指纹是基于现有的、小的、随机的电子芯片制造变化。该项目采用跨学科的方法，结合了统计领域和电路设计领域的最新进展，开发了芯片上的指纹结构，该结构在稳定性、实施成本和安全性方面进行了优化。稳定的片上指纹对随机制造变化最敏感，对温度、电压、噪声和老化等其他环境因素最不敏感。低成本的片上指纹是通过使用统计、架构和电路级技术来获得的，这些技术可以最大限度地提取熵。安全的芯片指纹可以抵御常见的攻击，比如逆向工程和模型构建。由于其跨学科的特点，该项目为电路识别建立了先进的统计分析和深亚微米设计之间急需的联系。这导致更好的PUF设计，适用于更广泛的应用程序：安全护照、防伪方案以及端点的安全性和信任。该项目包括研究和教育的强有力的整合。对于大学预科生和即将入学的大一学生，该项目在现有的校园工程项目的背景下，向他们介绍了可信赖的硬件。对于研究生，该项目提供了一个团队授课的课程，由电气工程系和统计系共享。

In a world where everybody and everything is electronically connected, identity is essential to support trustworthy transactions. This project investigates novel techniques to design and implement on-chip fingerprints. Such fingerprints establish the hardware identity of an electronic system. The on-chip fingerprints are based on the existing, small and random manufacturing variations of electronic chips. Using a cross-disciplinary approach that combines recent advances in the field of statistics with those in circuit design, this project develops on-chip fingerprint structures that are optimized for stability, implementation cost, and security. Stable on-chip fingerprints are maximally sensitive to random manufacturing variations, and minimally sensitive to other environmental factors such as temperature, voltage, noise, and aging. Low-cost on-chip fingerprints are obtained by using statistical, architectural, and circuit-level techniques that maximize the amount of extracted entropy. Secure on-chip fingerprints are resistant against common attacks such as reverse engineering and model building. Thanks to its cross-disciplinary character, this project establishes a much-needed link between advanced statistical analysis and deep-submicron design for the purpose of circuit identification. This leads to better PUF designs, applicable across a wider range of applications: secure passports, anti-counterfeiting schemes, and security and trust at the endpoints. The project includes strong integration of research and education. For pre-college and entering freshman students, the project offers an introduction to trusted hardware, in the context of existing on-campus programs that involve minorities in engineering. For graduate students, the project offers a team-taught course, shared between the electrical engineering department and the statistics department.