FerroCoin: Ferroelectric Tunnel Junction-Based True Random Number Generator

Swetaki Chatterjee, Nikhil Rangarajan, Satwik Patnaik, Dinesh Rajasekharan, Ozgur Sinanoglu, Yogesh Singh Chauhan

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we propose a Ferroelectric Tunnel Junction (FTJ)-based true random number generator (TRNG) that utilizes the stochastic domain switching phenomenon in ferroelectric materials. Ferroelectrics are promising for extracting randomness owing to their innate switching entropy in the multi-domain state. The random numbers generated by the proposed TRNG are shown to pass all the NIST SP 800-22 tests. The robustness of the proposed TRNG is also validated at various temperature and process corners. Important metrics such as power, bit rate, and energy/bit are calculated. This is the first comprehensive work demonstrating a ferroelectric-based TRNG with all these metrics. Compared to state-of-the-art TRNGs using other emerging technologies, we can achieve a higher bit rate with lower power consumption. We also perform material-level optimization with different ferroelectric materials, and showcase the trade-off between the bit rate and the power consumption. The proposed TRNG shows high robustness and reliability, and thus has the potential for implementing a low power on-chip solution.

Original languageEnglish (US)
Pages (from-to)1-6
Number of pages6
JournalIEEE Transactions on Emerging Topics in Computing
DOIs
StateAccepted/In press - 2022

Keywords

  • Domain switching
  • Entropy
  • ferroelectric tunnel junction
  • Generators
  • hardware security
  • Junctions
  • Nickel
  • Power demand
  • stochasticity
  • Switches
  • true random number generator
  • Voltage

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications

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