Pseudo-Random Number Generator Seed Update Mechanism
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Solution Overview
Problem
Existing pseudo-random number generators (PRNGs) are susceptible to predictability, especially in cryptographic applications, due to their deterministic nature and reliance on seed values, making them vulnerable to brute-force attacks and lacking in high randomness and low predictability requirements.
Innovation Solution
A method and system that utilize a processor to select and update seed values from various categories, including geographic locations, future times, unforeseeable certifiable values, and predictable future values, to generate pseudo-random numerical sequences, which are then used to produce outputs for applications such as cryptography and gaming, ensuring enhanced security and unpredictability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If software-based PRNGs are used, then speed and reproducibility are improved, but randomness quality and security are worsened due to deterministic nature and vulnerability to brute-force attacks
Solution Approach 1:
The patent combines software-based PRNG speed advantages with hardware-based RNG security advantages by using hardware random number generation to generate seed values that initialize the software PRNG. This hybrid approach merges the deterministic speed of software generation with the true randomness of hardware generation, resolving the contradiction between speed and randomness quality.
Solution Approach 2:
The hardware random number generator acts as an intermediary that provides true random seed values to the software PRNG. This intermediary component bridges the gap between deterministic software generation and nondeterministic hardware generation, allowing the system to achieve both speed (through software PRNG) and security (through hardware-derived seeds).
2Ease of manufacture
If traditional PRNGs with fixed seed values are used, then implementation simplicity is improved, but security against brute-force attacks is worsened
Solution Approach 1:
The patent makes the seed values dynamic by continuously updating them with new random values from hardware generation. Instead of using fixed, static seed values that are vulnerable to brute-force attacks, the system dynamically refreshes seeds, making the PRNG implementation both simple to execute and secure against attacks.
Solution Approach 2:
The system performs preliminary action by pre-generating secure random seed values using hardware random number generation before initiating the software PRNG. This preliminary hardware-based seed generation establishes a secure foundation that protects against future brute-force attacks while maintaining implementation simplicity.
3Reliability
If cryptographic security requirements are strictly enforced, then security is improved, but system complexity and computational overhead are worsened
Solution Approach 1:
The patent replaces complex cryptographic mechanisms with a simpler hardware-based random number generation approach. Instead of implementing complex cryptographic protocols and algorithms to achieve security, the system uses physical hardware randomness to generate secure seed values, substituting mechanical/cryptographic complexity with physical randomness.
Solution Approach 2:
The system changes the fundamental parameter of seed value generation from software-based deterministic algorithms to hardware-based nondeterministic generation. This parameter change achieves cryptographic security requirements without the associated complexity, as the security comes from the physical randomness source rather than computational complexity.
Data Source
AI summary
An improved pseudo-random number generator is introduced that has increased security due to higher randomness and lower predictability. The PRNG uses seed values that are based on a combination of various selectable values from the real-world that are typically made publicly available over a computer network (i.e., the Internet), such as: one or more weather conditions at a particular time or date and geographic location, a score of a sports event, a stock market index or ticker value, an election vote total, attendance at a cultural event, gross dollar sales from a movie release, and other such numerically quantifiable values that, individually and in combination, are impossible to exactly predict in advance, yet are precisely verifiable after the number-generating event using electronically-stored information. The improved pseudo-random number generator may be used for more secure determination of lottery outcomes and the like.