Random Number Generator Using Multiple Moduli Functions
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Solution Overview
Problem
Existing random number generators, particularly in cryptographic applications, face challenges in generating secure pseudo-random numbers that are resilient against attacks, as they can be vulnerable to cryptographic attacks like the Berlekamp-Massey algorithm, and combining independent sequences may not sufficiently increase security.
Innovation Solution
An electronic random number generator that uses multiple functions with different moduli, where each function evaluates a previously generated number modulo its associated modulus, and applies a combination function to the results to generate the next number in the sequence, ensuring contributions from incompatible mathematical structures to enhance security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If linear shift registers are used to generate random numbers, then the generation speed is fast and resources required are low, but security against cryptographic attacks is poor
Solution Approach 1:
The patent divides the random number generation process into multiple independent linear shift registers (first LSR and second LSR), each generating separate sequences. These sequences are then combined through non-linear functions to produce the final output. This segmentation allows each component to remain simple and fast while the combination provides enhanced security.
Solution Approach 2:
The patent combines multiple linear shift register sequences using non-linear combination functions (such as alternating step generator or shrinking generator logic) to create a composite random number sequence. This composite structure resists cryptographic attacks better than individual linear sequences while maintaining the efficiency of linear operations.
2Reliability
If two independent linear shift register sequences are combined, then the difficulty of cryptographic attack increases, but the device complexity increases
Solution Approach 1:
The patent employs dynamic control mechanisms where one linear shift register controls the operation of another (e.g., the first LSR controls the clocking or selection of the second LSR). This dynamic interaction creates complex behavior from simple components, enhancing security without requiring permanently active complex circuitry.
Solution Approach 2:
The patent introduces control sequences and selection mechanisms that act as intermediaries between the two linear shift registers. These intermediaries manage the combination process, allowing the system to achieve high security through coordinated interaction rather than direct complex coupling.
3Reliability
If multiple functions with different moduli are used, then security is enhanced, but the complexity of the generation process increases
Solution Approach 1:
The patent changes mathematical parameters (moduli) across different functions in the combination process. By using different moduli for different linear shift registers and their combination functions, the system creates mathematical incompatibility that resists attacks while maintaining computationally feasible operations through modular arithmetic.
Data Source
AI summary
An electronic random number generating device (100) for generating a sequence of random numbers, the electronic random number generating device comprising an electronic parameter storage (110) configured to store multiple functions and for each function of the multiple functions an associated modulus, not all moduli being equal, and an electronic function evaluation device (120) configured to generate an internal sequence of random numbers, the function evaluation device being configured to generate a next number in the internal sequence of random numbers by for each function of the multiple functions, evaluating the function for a previously generated value in the internal sequence of random numbers modulo the modulus associated with the evaluating function, so obtaining multiple evaluation results, and applying a combination function to the multiple evaluation results to obtain the next number in the internal sequence, and an output (140) configured to generate a next number in the sequence of random numbers from the generated next number in the internal sequence.