NoisFre: Noise-Tolerant Memory Fingerprints from Commodity Devices for Security Functions

Citation Author(s):
The University of Adelaide
Nanjing University of Science and Technology
CSIRO Data61
Damith C.
The University of Adelaide
Submitted by:
Yang Su
Last updated:
Thu, 06/30/2022 - 03:46
Data Format:
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Building hardware security primitives with on-device memory fingerprints is a compelling proposition given the ubiquity of memory in electronic devices, especially for low-end Internet of Things devices for which cryptographic modules are often unavailable. However, the use of fingerprints in security functions is challenged by the small, but unpredictable variations in fingerprint reproductions from the same device due to measurement noise. Our study formulates a novel and pragmatic approach to achieve highly reliable fingerprints from device memories. We investigate the transformation of raw fingerprints into a noise-tolerant space where the generation of fingerprints is intrinsically highly reliable. We derive formal performance bounds to support practitioners to easily adopt our methods for applications. Subsequently, we demonstrate the expressive power of our formalization by using it to investigate the practicability of extracting noise-tolerant fingerprints from commodity devices. Together with extensive simulations, we have employed 119 chips from five different manufacturers for extensive experimental validations. Our results, including an end-to-end implementation demonstration with a low-cost wearable Bluetooth inertial sensor capable of on-demand and runtime key generation, show that key generators with failure rates less than $10^-6$ can be efficiently obtained with noise-tolerant fingerprints with a single fingerprint snapshot to support ease-of-enrollment.


Folder organization


Data Collection Description

The bin file contains the start-up states of the whole 64 KiB SRAM block inside the nRF52832 Versatile Bluetooth 5.2 SoC.
An interested reader can find more detail about the evaluated chip in the datasheet in the root folder.
The test was taken at three temperatures -15°C, 25°C and 80°C, with 100 repeats at each temperature.

[1] Gao, Y., Su, Y., Nepal, S., & Ranasinghe, D. C. "NoisFre: Noise-Tolerant Memory Fingerprints from Commodity Devices for Security Functions." arXiv preprint arXiv:2109.02942, September 2021.

Funding Agency: 
Australian Research Council (DP140103448), National Natural Science Foundation of China (62002167), and Natural Science Foundation of JiangSu Province (BK20200461)