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Aging-Resilient SRAM-based True Random Number Generator for Lightweight Devices

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Abstract

A random number generator (RNG) is an important building block for cryptographic operations primarily to generate random nonces and secret keys. The power-up value of an SRAM array has been widely accepted as an entropy source for generating random numbers. However, only a few cells of the SRAM are truly random upon repeated power-ups; the vast majority of cells display a distinct bias from manufacturing process variations. Consequently, a relatively large SRAM array is required to obtain sufficient entropy for generating random numbers. Earlier research has proposed the use of controlled device aging at pre-deployment stage to enhance the initial entropy of an SRAM array. However, aging in the field can adversely affect the entropy and degrade randomness; we show here that any initial aging to increase SRAM entropy can even be counterproductive. Instead, we propose an SRAM-based random number generation approach, which continually manipulates device aging during operation to constantly maximize entropy for the entire deployment period. The key idea is to continually stress the SRAM cells in their power-up states at regular intervals. This helps counteract the aging caused by the random memory states that occur during operation. Silicon results are presented to validate our proposed approach.

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Acknowledgments

This work was supported in parts by the National Science Foundation under Grant Numbers CNS–1755733 and CCF– 1527049. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, USA

    Wendong Wang, Ujjwal Guin & Adit Singh

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  1. Wendong Wang
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  2. Ujjwal Guin
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  3. Adit Singh
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Correspondence to Wendong Wang.

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Responsible Editor: M. B. Tahoori

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Wang, W., Guin, U. & Singh, A. Aging-Resilient SRAM-based True Random Number Generator for Lightweight Devices. J Electron Test 36, 301–311 (2020). https://doi.org/10.1007/s10836-020-05881-6

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