A dynamically configurable LFSR-based PUF design against machine learning attacks
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A dynamically configurable LFSR‑based PUF design against machine learning attacks Shen Hou1,2 · Ding Deng1 · Zhenyu Wang1 · Jiahe Shi1 · Shaoqing Li1 · Yang Guo1 Received: 14 June 2020 / Accepted: 4 November 2020 © China Computer Federation (CCF) 2020
Abstract Physical unclonable function (PUF), a reliable and lightweight physical security primitive for secret key generation and antitampering. Strong PUF is an important PUF classification that provides a large “Challenge-Response” pairs (CRP) space for device authentication. However, none of the existing PUF constructions is both machine learning (ML) attack resistant and sufficiently lightweight to fit the low-end internet of things and embedded devices. A lightweight composition PUF design, Shift Register based PUF (SRPUF), is proposed in which the time delay performance is sacrificed to make the PUF structure variable and difficult to derive a stable model. A linear feedback shift register (LFSR) is used to de-synchronized the input challenges and output responses of the SRPUF. The LFSR can be configured dynamically to provide a high entropy source and large enough CRP space. The SRPUF is simulated in Python then implemented on a 28 nm FPGA. The experimental results show that the uniformity and uniqueness of the PUF is 49.8%, 49.9%, which is close to the ideal value, and the hardware overhead is small. Meanwhile, it shows excellent resistance to several popular ML attack methods. This new PUF design idea is suitable for resource-constrained and time delay-insensitive applications. Keywords Hardware security · Physical unclonable functions (PUFs) · Linear feedback shift register · Lightweight · Modeling attack
1 Introduction In recent years, with the development of wireless Internet, mobile Internet and internet of things (IoT) devices have entered all aspects of industry and people’s lives. The number of IoT devices is increasing rapidly, and Gartner predicts that the total number of IoT devices will reach 20.4 billion by 2020 (Ganguli and Friedman 2020). Embedded microprocessors, which are the core of IoT devices, face new security challenges, such as over-manufacturing, tampering with software, and hardware invasive attacks (Deng et al. 2020). These security problems are difficult to resolve with traditional security measures due to the difference between the IoT architecture and the traditional Internet. At the same time, for most IoT devices, their resources are limited. * Shen Hou [email protected] 1
School of Computer, National University of Defense Technology, Changsha, China
Department of Reconnaissance Intelligence, Information Engineering University, Luoyang, China
2
Integrating security modules in them will increase hardware overhead, which may cause some problems (Huang et al. 2011). Therefore, the development of new lightweight hardware security primitives as a root of trust (RoT), providing security services such as key generation and authentication for resource-constrained devices has become a very attractive res
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