相关论文: Design and Implementation of a High Quality and Hi…

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,…

As a vital security primitive, the true random number generator (TRNG) is a mandatory component to build roots of trust for any encryption system. However, existing TRNGs suffer from bottlenecks of low throughput and high area-energy…

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…

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…

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…

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,…

To increase the number of wireless devices, e.g., mobile or IoT terminals, cryptosystems are essential for secure communications. In this regard, random number generation is crucial because the appropriate function of cryptosystems relies…

Random number generation is an important task in a wide variety of critical applications including cryptographic algorithms, scientific simulations, and industrial testing tools. True Random Number Generators (TRNGs) produce truly random…

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…

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…

The aim of this paper is to present a new design for a pseudorandom number generator (PRNG) that is cryptographically secure, passes all of the usual statistical tests referenced in the literature and hence generates high quality random…

Random number generation is a key technology that is useful in a variety of ways. Random numbers are often used to generate keys for data encryption. Random numbers generated at a sufficiently long length can encrypt sensitive data and make…

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 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…

Quantum Random Number Generators (QRNGs) emerged as a promising solution for generating truly random numbers. In the present article, we give an overview of QRNGs highlighting the merits and demerits of various strategies briefly. Then…

High quality random numbers are necessary in the modern world. Ranging from encryption keys in cyber security to models and simulations for scientific use: it's important that these random numbers are of high quality and quickly attainable.…

Quantum random number generators (QRNGs) produce random numbers based on the intrinsic probabilistic nature of quantum mechanics, making them true random number generators (TRNGs). In this paper, we design and fabricate an embedded QRNG…

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…

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…

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…