A true random number generator based on nanowire-edge crossing memristors for image encryption

Area of Science:

• Materials Science
• Electrical Engineering
• Computer Science

Background:

• True random numbers are vital for information security and cryptography.
• Existing methods may have limitations in stability or unpredictability.

Purpose of the Study:

• To develop a stable and secure true random number generator (TRNG) using memristor switching.
• To demonstrate the application of this TRNG in image encryption and secure transmission.

Main Methods:

• Fabrication of a TRNG circuit using silicon nanowires (SiNWs) and conductive filaments (CFs) in SiO2.
• Utilizing the stochastic switching behavior of CFs for random number generation.
• Testing generated numbers with 15 NIST statistical tests and evaluating image encryption using YOLO model.

Main Results:

• The SiNW-edge crossing TRNG demonstrated stable memristor switching for long-term random number generation.
• Generated random numbers passed all 15 NIST statistical tests without post-processing.
• Encrypted images showed high uniqueness and non-reproducibility, with successful decryption and minimal data loss.

Conclusions:

• The NW-edge crossing TRNG offers a secure and stable hardware encryption solution.
• This approach is effective for image privacy and secure data transmission.
• The device leverages controlled nanoscale memristor switching for reliable random number generation.