True Random Number Generator (TRNG)

The essence of the solution (what it concerns):

This invention introduces a revolutionary True Random Number Generator (TRNG) that utilizes two distinct sources of randomness: the butterfly effect (chaos theory) and metastability. Unlike traditional designs that depend on stable operating conditions, this generator leverages constant instability to deliver high-entropy random numbers while resisting aggressive active side-channel attacks. Its adaptability allows it to seamlessly integrate into IoT devices and professional cryptographic accelerators, providing secure and statistically robust random number generation.

PROBLEM:

Random number generators (RNGs) play a vital role in cryptography, authentication, and secure communication. However, conventional RNGs often struggle with key challenges:

1. Low Entropy: Many RNGs amplify limited randomness, leading to outputs that may lack true unpredictability.
2. Environmental Sensitivity: Existing designs frequently require stable working conditions or precise initial parameters, making them prone to active attacks.
3. High Complexity: Advanced RNGs often rely on dedicated hardware components, which increase implementation costs and limit compatibility with resource-constrained devices. These limitations restrict the effectiveness and scalability of current RNG solutions, especially for applications requiring high security or seamless integration with IoT and programmable circuits.

SOLUTION:

The TRNG solves these challenges with a novel design that innovatively combines chaotic behavior and metastability:

1. Chaos Theory-Based Randomness: Utilizing the butterfly effect, the generator amplifies instabilities during switching moments, achieving infinite amplification of small random processes. Unlike other chaotic RNGs, this design incorporates a phase-based feedback loop to enhance randomness.
2. Metastability-Based Randomness: The generator employs metastable circuits with random initial conditions, eliminating the need for programmable delays or clock managers. This simplifies implementation across a wide range of programmable circuits.
3. Constant Instability: The generator operates under intentionally unstable conditions, making it resistant to active side-channel attacks that exploit predictable behavior.
4. Customizable Design: Multiple possible implementation ways  and innovative control methods allow the generator to meet various target requirements, ensuring flexibility for diverse applications.

APPLICATION:

The TRNG is designed for any application requiring reliable, high-quality random number generation. It is particularly suited for:

1. Cryptography: Generation of unique cryptographic keys; Random seeds for encryption algorithms; Authentication and secure communication protocols.
2. Statistics and Simulations: Random number generation with strong statistical properties, ideal for scientific modeling and probabilistic computing.
3. IoT Devices: Seamless integration into routers, smart devices, and communication modules, enhancing security for large-scale connected ecosystems.
4. Specialized Hardware: VLSI coprocessors, smart cards, RFID systems, and network equipment.

Target platforms include silicon-level VLSI implementations, programmable circuits (FPGA, CPLD), and discrete-component designs. This versatility makes the TRNG applicable to both specialized and everyday circuits.

TECHNOLOGY:

The TRNG features cutting-edge innovations in random number generation:

1. Chaos Theory Integration: The chaotic system state variable is harnessed through short-term phase measurements, amplifying minor random phase differences and delivering high entropy in the output stream.
2. Metastability Circuits: The metastable circuit is fed by a chaotic system state variable without relying on precise initial conditions, removing the need for programmable delays or digital clock management. This ensures compatibility with nearly any programmable circuit, even in simple designs.
3. Innovative Ring Oscillators: The generator includes advanced constructions of switchable-length ring oscillators, offering precise control and enabling customizable configurations to meet specific requirements.
4. Resilient Design: By operating under constant instability, the generator achieves robust resistance to side-channel attacks, enhancing the security of cryptographic applications.

SOLUTION ADVANTAGES:

1. High Entropy: The use of chaos theory and metastability ensures truly random outputs with superior statistical properties.
2. Resistance to Attacks: Constant instability makes the generator immune to active side-channel attacks, providing strong security for sensitive applications.
3. Ease of Implementation: The design eliminates the need for complex hardware components, allowing for low-cost, scalable integration in programmable circuits (FPGA, CPLD) and VLSI designs.
4. Wide Compatibility: Supports both advanced and resource-constrained platforms, including IoT devices, RFID systems, and network equipment.
5. Customizable Configurations: Multiple design variants allow the generator to meet diverse requirements, ensuring flexibility across applications.
6. Cost Efficiency: The generator’s simplicity reduces implementation costs, making high-quality random number generation accessible to a broader range of industries.