Enhancing IoT security with threshold switching-based unified security primitives

In the era of big data and Internet of Things (IoT), the surge in data volume and widespread interconnectivity of devices make hardware a key node in a vast network ecosystem. Developing state-of-the-art secure IoT hardware is necessary and critical. In this paper, we successfully realized a unified security hardware integrating Physically unclonable function (PUF) and true random number generator (TRNG) functions by constructing a 32× 32 1T1R array based on threshold switching (TS) memristor cells. Through detailed analysis of the chemical properties of FeO<i><sub>x</sub></i>films and the electrical properties of TS memristors, we verified that the prepared TS devices have good cyclic stability and randomness. Leveraging these characteristics, we implemented a PUF system and effectively deployed a TRNG relying on the CTR_DRBG algorithm. Notably, the generated PUF exhibits a Hamming Weight of 0.508 with the standard deviation of 0.062, along with an Intra-Hamming Distance of 0.00012 with the standard deviation of 0.142 and an Inter-Hamming Distance of 0.496 with the standard deviation of 0.073. Moreover, we conducted a baking test on the samples for 100 h at each temperature point, with intervals of 25 °C within the 25 °C-125 °C range. The resulting bit-error rate (BER) of the generated PUF remains below 1.5%, which clearly attests to the PUF's remarkable uniformity, uniqueness, and robustness. Subsequently, we subjected the generated random numbers to the National Institute of Standards and Technology-900 test. The results revealed that the<i>p</i>-values of all test items exceeded 0.01, a strong indication of the outstanding randomness of the generated random numbers. Compared with other similar works, the energy consumption per bit is reduced by more than 30%, and the rate of generating random numbers is increased by more than 20%. The proposed unified security hardware not only demonstrates the potential application of TS memristor in hardware security, but also provides new ideas for solving the integration and energy efficiency problems of security hardware in IoT devices.

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Publication Details

Journal
Nanotechnology
Published
2025-02-24
DOI
https://doi.org/10.1088/1361-6528/adb980
Citations
3
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
2.19

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article

Enhancing IoT security with threshold switching-based unified security primitives

Jiabao Sun, Dawei Gao, Yishu Zhang, Xuemeng Fan et al.
3 citations
Nanotechnology
Advanced Memory and Neural Computing
2.19
article

Enhancing IoT security with threshold switching-based unified security primitives

Jiabao Sun, Dawei Gao, Yishu Zhang, Xuemeng Fan, Qisheng Luo, Guobin Zhang, Jiajun Kan
article en
3 citations

Abstract

In the era of big data and Internet of Things (IoT), the surge in data volume and widespread interconnectivity of devices make hardware a key node in a vast network ecosystem. Developing state-of-the-art secure IoT hardware is necessary and critical. In this paper, we successfully realized a unified security hardware integrating Physically unclonable function (PUF) and true random number generator (TRNG) functions by constructing a 32× 32 1T1R array based on threshold switching (TS) memristor cells. Through detailed analysis of the chemical properties of FeO<i><sub>x</sub></i>films and the electrical properties of TS memristors, we verified that the prepared TS devices have good cyclic stability and randomness. Leveraging these characteristics, we implemented a PUF system and effectively deployed a TRNG relying on the CTR_DRBG algorithm. Notably, the generated PUF exhibits a Hamming Weight of 0.508 with the standard deviation of 0.062, along with an Intra-Hamming Distance of 0.00012 with the standard deviation of 0.142 and an Inter-Hamming Distance of 0.496 with the standard deviation of 0.073. Moreover, we conducted a baking test on the samples for 100 h at each temperature point, with intervals of 25 °C within the 25 °C-125 °C range. The resulting bit-error rate (BER) of the generated PUF remains below 1.5%, which clearly attests to the PUF's remarkable uniformity, uniqueness, and robustness. Subsequently, we subjected the generated random numbers to the National Institute of Standards and Technology-900 test. The results revealed that the<i>p</i>-values of all test items exceeded 0.01, a strong indication of the outstanding randomness of the generated random numbers. Compared with other similar works, the energy consumption per bit is reduced by more than 30%, and the rate of generating random numbers is increased by more than 20%. The proposed unified security hardware not only demonstrates the potential application of TS memristor in hardware security, but also provides new ideas for solving the integration and energy efficiency problems of security hardware in IoT devices.

NanotechnologyVol. 36(15)
University of Science and Technology of China (CN), Hangzhou Vocational and Technical College (CN), Advanced Micro-Fabrication Equipment (China) (CN), Zhejiang Medicine (China) (CN), Hangzhou Dianzi University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 13%
Advanced Memory and Neural Computing
2.19
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