Bi₂O₂Se-Based True Random Number Generator for Security Applications.

Area of Science:

• Materials Science
• Cybersecurity
• Semiconductor Devices

Background:

• The proliferation of Internet of Things (IoT) devices generates vast amounts of data, creating significant security vulnerabilities.
• Current encryption methods often rely on software-based pseudorandom number generators susceptible to attacks.
• True Random Number Generators (TRNGs) utilizing physical phenomena offer a more robust alternative for secure data handling.

Purpose of the Study:

• To demonstrate a novel Bi2O2Se-based memristive device as a True Random Number Generator (TRNG) for advanced security applications.
• To investigate the intrinsic stochasticity and complexity of Bi2O2Se memristors for reliable random number generation.
• To evaluate the resilience of the generated random numbers against machine learning-based prediction.

Main Methods:

• Fabrication and characterization of a Bi2O2Se-based memristive device.
• Utilizing the device's vertical surface resistive switching for analogue/digital random number generation.
• Assessing the randomness quality and unpredictability of the generated numbers.

Main Results:

• The Bi2O2Se memristor exhibits intrinsic stochasticity and complexity due to its unique material properties and interface.
• The device successfully generates both analogue and digital random numbers.
• The random number generation process demonstrated resilience against machine learning prediction, indicating high security potential.

Conclusions:

• Bi2O2Se-based memristive devices represent a promising platform for developing highly secure TRNGs.
• The unique properties of Bi2O2Se contribute to intrinsic randomness, enhancing security for IoT and communication systems.
• This approach offers a hardware-based solution to overcome the limitations of software-based security protocols.