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Memristive True Random Number Generator for Security Applications
Xianyue Zhao1,2, Li-Wei Chen3, Kefeng Li1,2
1Institute for Solid State Physics, Friedrich Schiller University Jena, 07743 Jena, Germany.
Sensors (Basel, Switzerland)
|August 10, 2024
Summary
Memristor true random number generators (TRNGs) offer simpler circuits and lower power consumption than CMOS alternatives. This study examines their entropy sources and highlights challenges in optimization for future security applications.
Area of Science:
- Materials Science
- Electrical Engineering
- Computer Science
Background:
- Memristors, theorized in 1971 and realized in 2008, are key components in novel electronic devices.
- True Random Number Generators (TRNGs) are crucial for secure cryptographic applications.
Purpose of the Study:
- To explore and optimize memristor-based TRNGs.
- To evaluate various entropy sources for high-quality random number generation.
- To compare memristor TRNGs with traditional CMOS-based TRNGs.
Main Methods:
- Analysis of memristor TRNG evolution and entropy sources.
- Comparative study with CMOS-based TRNGs.
- Case study using electroless YMnO3 (YMO) memristors.
Main Results:
- Memristor TRNGs exhibit simpler circuitry and reduced power consumption compared to CMOS TRNGs.
- Electroless YMO memristors demonstrate potential as effective entropy sources for unpredictable random numbers.
- Identified security properties of memristor-based TRNGs.
Conclusions:
- Memristor TRNGs present a promising alternative for next-generation security applications.
- Further research is needed for post-processing algorithm optimization and long-term reliability.
- Addressing these challenges will enhance the viability of memristor TRNGs.
