A noise-based IC random number generator for applications in cryptography

By C. Petrie, J. Connelly. 2000

475 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/d5c74c6a4ce481260e3dbf7ab51579bd7972bc6f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Abu Sebastian
2. Wei Dang Lu
3. Qing Wu
4. Bryan Perozzi
5. Chengqi Zhang
6. William L. Hamilton

In Computational Theory and Mathematics

1. S. Savel’ev
2. Wei Dang Lu
3. Abu Sebastian
4. M. Le Gallo

In Computer Vision and Pattern Recognition

1. Wei Dang Lu
2. Abu Sebastian
3. Meilin Liu
4. Qing Wu

Citations in the corpus

• A novel true random number generator based on a stochastic diffusive memristor (2017, background): “For example, thermal noise is often exploited by TRNGs via oscillator jitter 4 , resistor-ampli fi er-Analog/Digital converter chains 5 , or metastable elements with capacitive feed-back 6 .”
• Memristive technologies for data storage, computation, encryption, and radio-frequency communication (2022, background): “In modern TRNGs, a frequently adopted entropy source is thermal noise, which can be harvested from either a large resistor, or jitter inringoscillators,orthemodulationsit induces in analog-to-digital converters ( 90 – 92 ).”