RRAM Gaussian Sampling Apparatus for Post-Quantum Cryptography
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Solution Overview
Problem
Existing Gaussian sampling devices face high implementation area and speed overhead due to the use of real random number generators and Field-Programmable Gate Arrays (FPGAs) or software circuits.
Innovation Solution
A Gaussian sampling apparatus based on Resistive Random Access Memory (RRAM) is developed, utilizing a resistive switching layer between electrodes and a sampling controller to perform erase and program operations, eliminating the need for real random number generators and leveraging fast read/write capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a real random number generator is used for Gaussian sampling, then the quality of random numbers is improved, but the implementation area and speed overhead increase significantly
Solution Approach 1:
The patent extracts the Gaussian sampling function from traditional implementations using real random number generators and FPGAs, and relocates it to RRAM-based memory cells. By utilizing the inherent resistance variations in RRAM cells during program/erase operations, the system eliminates the need for separate random number generation hardware, thereby reducing implementation area overhead while maintaining sampling quality
Solution Approach 2:
The patent replaces the mechanical/electronic system of real random number generators with a memory-based system utilizing RRAM cells. The physical resistance states of RRAM cells, which naturally exhibit variability during programming operations, substitute for dedicated random number generation circuitry, achieving both area reduction and functional integration
2Reliability
If traditional Gaussian sampling methods are used, then the sampling function is achieved, but the implementation area overhead is high
Solution Approach 1:
The patent makes RRAM memory cells perform multiple functions: they serve both as storage elements and as Gaussian sampling devices. The same RRAM cells used for data storage are utilized to generate Gaussian-distributed random numbers through their program/erase operations, eliminating the need for separate sampling hardware and reducing overall implementation area
Solution Approach 2:
The patent merges the Gaussian sampling function with the memory storage function by using RRAM cells for both purposes. The resistance variations that occur during normal memory operations are harnessed to produce Gaussian-distributed samples, combining what were previously separate functions into a single integrated system
3Adaptability or versatility
If FPGAs or software circuits are used for Gaussian sampling, then the sampling capability is achieved, but the implementation area overhead remains high
Solution Approach 1:
The patent utilizes the transient resistance states of RRAM cells during program/erase operations as a disposable resource for generating random samples. These resistance variations, which occur naturally during memory operations, are captured and used for Gaussian sampling before the cells return to their stable states, effectively using temporary physical phenomena without requiring permanent dedicated sampling circuitry
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The RRAM-based solution achieves high integration and fast operation, providing a cost-effective and efficient means for generating Gaussian error data essential for Post-Quantum Cryptography, particularly in lattice-based cryptography, without the overhead of traditional methods.
Implementation Method 1
The resistive switching layer may be configured to switch a resistance state from a high resistance state to a low resistance state when the set voltage is applied to the upper electrode and the lower electrode, and switch the resistance state from a low resistance state to a high resistance state when the reset voltage is applied to the upper electrode and the lower electrode.
Data Source
AI summary
Disclosed herein are a Gaussian sampling apparatus and method based on resistive RAM. The Gaussian sampling apparatus based on resistive RAM includes Resistive RAM (RRAM) in which a resistive switching layer is disposed between an upper electrode and a lower electrode, and a sampling controller, wherein the sampling controller is configured to perform an operation corresponding to an erase command of applying a reset voltage to the RRAM when a Gaussian error request is received from an outside of the Gaussian sampling apparatus, perform an operation corresponding to a program command of applying a set voltage to the RRAM after the operation corresponding to the erase command has been completed, perform an operation of reading resistance data from the RRAM, and provide a response to the outside of the Gaussian sampling apparatus by transmitting the resistance data of the RRAM as Gaussian error data.