Related papers: DR-STRaNGe: End-to-End System Design for DRAM-base…

We propose a new DRAM-based true random number generator (TRNG) that leverages DRAM cells as an entropy source. The key idea is to intentionally violate the DRAM access timing parameters and use the resulting errors as the source of…

True random number generator (TRNG) plays a vital role in a variety of security applications and protocols. The security and privacy of an asset rely on the encryption, which solely depends on the quality of random numbers. Memory chips are…

Quality randomness is fundamental to cryptographic operations but on embedded systems good sources are (seemingly) hard to find. Rather than use expensive custom hardware, our ERHARD-RNG Pseudo-Random Number Generator (PRNG) utilizes…

Random number generation (RNG) is a crucial element in security protocols, and its performance and reliability are critical for the safety and integrity of digital systems. This is especially true in 5G networks with many devices with low…

True Random Number Generators (TRNGs) play a fundamental role in hardware security, cryptographic systems, and data protection. In the context of Deep NeuralNetworks (DNNs), safeguarding model parameters, particularly weights, is critical…

Prior works propose SRAM-based TRNGs that extract entropy from SRAM arrays. SRAM arrays are widely used in a majority of specialized or general-purpose chips that perform the computation to store data inside the chip. Thus, SRAM-based TRNGs…

True random number generators (TRNG) sample random physical processes to create large amounts of random numbers for various use cases, including security-critical cryptographic primitives, scientific simulations, machine learning…

As a fundamental phenomenon in nature, randomness has a wide range of applications in the fields of science and engineering. Among different types of random number generators (RNG), quantum random number generator (QRNG) is a kind of…

High-quality random numbers are very critical to many fields such as cryptography, finance, and scientific simulation, which calls for the design of reliable true random number generators (TRNGs). Limited by entropy source, throughput,…

Random number generators (RNG) are an important resource in many areas: cryptography (both quantum and classical), probabilistic computation (Monte Carlo methods), numerical simulations, industrial testing and labeling, hazard games,…

Pseudo-random number generators (PRNGs) are essential in a wide range of applications, from cryptography to statistical simulations and optimization algorithms. While uniform randomness is crucial for security-critical areas like…

Random Number Generators (RNGs) are crucial for applications ranging from cryptography to simulations. Depending on the source of randomness, RNGs are classified into Pseudo-Random Number Generators (PRNGs), True Random Number Generators…

In this work, we experimentally demonstrate that it is possible to generate true random numbers at high throughput and low latency in commercial off-the-shelf (COTS) DRAM chips by leveraging simultaneous multiple-row activation (SiMRA) via…

The emerging magneto-resistive RAM (MRAM) has considerable potential to become a universal memory technology because of its several advantages: unlimited endurance, lower read/write latency, ultralow-power operation, high-density, and CMOS…

A Pseudo-Random Number Generator (PRNG) is any algorithm generating a sequence of numbers approximating properties of random numbers. These numbers are widely employed in mid-level cryptography and in software applications. Test suites are…

Random number generation is fundamental for many modern applications including cryptography, simulations and machine learning. Traditional pseudo-random numbers may offer statistical unpredictability, but are ultimately deterministic. On…

Even if the output of a Random Number Generator (RNG) is perfectly uniformly distributed, it may be correlated to pre-existing information and therefore be predictable. Statistical tests are thus not sufficient to guarantee that an RNG is…

Random number generators (RNG) are essential elements in many cryptographic systems. True random number generators (TRNG) rely upon sources of randomness from natural processes such as those arising from quantum mechanics phenomena. We…

A TPM (trusted platform module) is a chip present mostly on newer motherboards, and its primary function is to create, store and work with cryptographic keys. This dedicated chip can serve to authenticate other devices or to protect…

AI-Hybrid TRNG is a deep-learning framework that extracts near-uniform entropy directly from physical noise, eliminating the need for bulky quantum devices or expensive laboratory-grade RF receivers. Instead, it relies on a low-cost,…