Leveraging Aging Effect to Improve SRAM-based True Random Number Generators

Saman Kiamehra, Mohammad Saber Golanbarib and Mehdi B. Tahooric
Karlsruhe Institute of Technology, Karlsruhe, Germany.


The start-up value of SRAM cells can be used as the random number vector or a seed for the generation of a pseudo random number. However, the randomness of the generated number is pretty low since many of the cells are largely skewed due to process variation and their start-up value leans toward zero or one. In this paper, we propose an approach to increase the randomness of SRAM-based True Random Number Generators (TRNGs) by leveraging transistor aging impact. The idea is to iteratively power-up the SRAM cells and put them under accelerated aging to make the cells less skewed and hence obtaining a more random vector. The simulation results show that the min-entropy of SRAM-based TRNG increases by 10X using this approach.

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