Lightweight Strategy for XOR PUFs as Security Primitives for Resource-constrained IoT device
Gaoxiang Li, Khalid T. Mursi, Yu Zhuang

TL;DR
This paper proposes a lightweight XOR-PUF strategy that balances hardware cost, energy efficiency, and security against machine learning attacks for resource-constrained IoT devices.
Contribution
It introduces a novel approach combining architecture parameters and usage strategies to enhance XOR-PUF security and efficiency.
Findings
XOR-PUFs with the proposed strategy resist advanced machine learning attacks.
The approach maintains high intra- and inter-device performance.
Hardware and energy costs are reduced compared to traditional methods.
Abstract
Physical Unclonable Functions (PUFs) are promising security primitives for resource-constrained IoT devices. And the XOR Arbiter PUF (XOR-PUF) is one of the most studied PUFs, out of an effort to improve the resistance against machine learning attacks of probably the most lightweight delay-based PUFs - the Arbiter PUFs. However, recent attack studies reveal that even XOR-PUFs with large XOR sizes are still not safe against machine learning attacks. Increasing PUF stages or components and using different challenges for different components are two ways to improve the security of APUF-based PUFs, but more stages or components lead to more hardware cost and higher operation power, and different challenges for different components require the transmission of more bits during operations, which also leads to higher power consumption. In this paper, we present a strategy that combines the…
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