Conclusion
In summary, we have successfully developed a detailed theoretical and experimental TRNG using high-frequency noise in 130-nm embedded RRAM. Binary bit sequences generated by our RRAM-based TRNG are evaluated through min-entropy and pass all the NIST SP 800-22 randomness tests. Moreover, it shows excellent temperature stability; thus, it can be applied in various harsh environments. The high-speed, low-power RRAM-based TRNG demonstrated here shows great potential for communication data security.
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References
Tseng P H, Lee M H, Lin Y H, et al. ReRAM-based pseudo-true random number generator with high throughput and unpredictability characteristics. IEEE Trans Electron Dev, 2021, 68: 1593–1597
Lin B, Gao B, Pang Y, et al. A high-speed and high-reliability TRNG based on analog RRAM for IoT security application. In: Proceedings of IEEE International Electron Devices Meeting (IEDM), San Francisco, 2019
Feng Y, Huang P, Zhao Y, et al. Improvement of state stability in multi-level resistive random-access memory (RRAM) array for neuromorphic computing. IEEE Electron Dev Lett, 2021, 42: 1168–1171
Puglisi F M, Pavan P, Larcher L, et al. Statistical analysis of random telegraph noise in HfO2-based RRAM devices in LRS. Solid-State Electron, 2015, 113: 132–137
Pelgrom M J M, Duinmaijer A C J, Welbers A P G. Matching properties of MOS transistors. IEEE J Solid-State Circ, 1989, 24: 1433–1439
Acknowledgements
This work was supported in part by National Key Research and Development Program of China (Grant No. 2019YFB2205100), National Natural Science Foundation of China (Grant Nos. 61874006, 61834001), and 111 Project Program (Grant No. B18001).
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Supporting information Appendixes A–C. The supporting information is available online at https://info.scichina.com and https://link.springer.com. The supporting materials are published as submitted, without typesetting or editing. The responsibility for scientific accuracy and content remains entirely with the authors.
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Song, S., Huang, P., Shen, W. et al. A 3.3-Mbit/s true random number generator based on resistive random access memory. Sci. China Inf. Sci. 66, 219402 (2023). https://doi.org/10.1007/s11432-022-3640-0
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DOI: https://doi.org/10.1007/s11432-022-3640-0