National Institute Of Standards And Technology Research Articles

Analysis of seven micronutrients in breast milk of lactating mothers from the Central Region of Ghana using epithermal neutron activation

Background: Breast milk contains various micronutrients which nourishes a baby with nutrition, and therefore the endorsement for exclusive breastfeeding during the first six months after birth. Such micronutrients, if in excess, can have adverse effects on the baby.
 Objective: The levels of seven micronutrients in breast milk obtained from 27 lactating mothers in the Cape Coast Metropolitan area have been determined using Epithermal Neutron Activation Analysis (ENAA). This technique was used because it is suitable for performing both qualitative and quantitative multi-nutritional analyses on samples, and offers accuracies and sensitivities superior to those attainable by other methods.
 Materials and Methods: During the analysis, a- 3 mm thick flexible boron was used to cut-off thermal neutrons so as to assess epithermal neutrons, thereby creating an activation energy which measured the levels of micronutrients in the breast milk. The standard reference materials used were the International Atomic Energy Agency (IAEA)-336; IAEA-407, IAEA-350 and National Institute of Standard and Technology (NIST) USA SRM 1577b. The Relative standardization method was used in the quantification of the micronutrients, with an accuracy of about 94.7 %. The micronutrients are Sodium (Na), Magnesium (Mg), Potassium (K), Calcium (Ca), Manganese (Mn), Copper (Cu) and Iodine (I).
 Results: Except for iodine which had levels below the recommended dietary allowance (RDA), the remaining micronutrients had levels above the upper limit of the RDA, with Manganese being the highest.
 Conclusion: The levels recorded are directly linked to the food intake of the mothers, and therefore the need for pregnant and lactating mothers to be mindful about what they eat. Children could be exposed to metabolic disorders and diseases as a result of such high levels.

An optimized 128-bit cellular automata-based hash function for authentication of data at rest and in transit

The cryptographic hash functions are the most fundamental cryptographic concept. These functions are used as basic building blocks for digital signatures and message authentication. Boolean functions are the core of hash functions. These functions are expected to provide pseudo-randomness as well as input sensitivity. Cellular automata are a form of Boolean function that exhibits strong cryptography properties as well as chaotic behavior. This paper proposes a hash function, designed on the principle of cellular automata. The proposed algorithm is secure and meets the requirements for a successful hashing scheme. The hash function has strong statistical and cryptographic characteristics, according to the findings of the avalanche test and the National Institute of Standards and Technology (NIST) Statistical Test Suite. The modularity of different operations of this algorithm makes it suitable for a high-capacity processing environment to produce efficient performance.

COPMA: Compact and Optimized Polynomial Multiplier Accelerator for High-Performance Implementation of LWR-Based PQC

The rapid progress in quantum computing has initiated a new round of cryptographic innovation, that is, developing postquantum cryptography (PQC) to resist attacks from well-established quantum computers. In this brief, we propose a novel compact and optimized polynomial multiplier accelerator (COPMA) for high-performance implementation of learning-with-rounding (LWR)-based PQC. As not many LWR-based PQC schemes are available in the literature, we have just used Saber, the National Institute of Standards and Technology (NIST) third-round PQC standardization finalist, as a typical case study example. First of all, we have formulated the polynomial multiplication, the major component of Saber, into a novel “subpolynomial”-based processing format for compact computation (yet has the potential for fast operation). Then, we have designed the proposed algorithm into an area-efficient polynomial multiplication hardware accelerator with high-frequency operational capability. Finally, we have verified the efficiency of the developed COPMA and have deployed it to build a cryptoprocessor. The implementation and analysis demonstrate the superior performance of the proposed COPMA. The proposed strategy is highly efficient and can be extended to build other PQC hardware accelerators.

A 325F 2 Physical Unclonable Function Based on Contact Failure Probability With Bit Error Rate < 0.43 ppm After Preselection With 0.0177% Discard Ratio

Preselection methods in which unstable bitcells are discarded are widely used to enhance the stability of the physical unclonable function (PUF). If the discard range of the preselection is too narrow, all unstable bitcells cannot be discarded, whereas, if the discard range is too wide, the PUF circuit area increases because the number of redundant bitcells should increase. Moreover, the discard range of most previous PUFs is not determined by theoretical analysis but rather by repeated measurements, which requires a long test time and cannot determine the accurate discard range to guarantee the PUF stability. This article demonstrates an efficient preselection method to determine the discard range through a theoretical analysis of the PUF entropy source for the PUF based on contact failure probability (contact PUF). After this preselection with the discard ratio of 0.0177%, no PUF responses changed among 2 367 040 bits from 1138 chips, i.e., bit error rate <inline-formula> <tex-math notation="LaTeX">$&lt;$</tex-math> </inline-formula>0.43 ppm, in seven harsh environmental tests regulated by the Joint Electron Device Engineering Council (JEDEC) standard. The proposed preselection method also enables the contact PUF to be implemented in a small area due to the low discard ratio. A small-area design methodology of contact PUF bitcells is also proposed. The PUF bitcell area per bit is 325<inline-formula> <tex-math notation="LaTeX">$F^{2}$</tex-math> </inline-formula>, the smallest area compared to previous PUFs. The contact PUF with the proposed preselection applied is fabricated in 100-nm CMOS technology. It achieves 0.4999 of uniqueness and 0.9942 of Shannon entropy and passes all applicable randomness tests stipulated by the National Institute of Standards and Technology (NIST) SP800-22.

Multi-Level Pooling Model for Fingerprint-Based Gender Classification

It has been widely reported that CNN (Convolutional Neural Network) has shown satisfactory results in classifying images. The strength of CNN lies in the type and the number of layers that construct it. However, the most apparent drawbacks of CNN are the requirement for a large labeled dataset and its lengthy training time. Although datasets are available, labeling that data is a significant problem. This work mimics the CNN model but only utilizes its pooling layers. The novelty of this model is removing convolution layers and directly processing fingerprint images using pooling layers. Three pooling layer models, namely maximum pooling, average pooling, and minimum pooling, are used to generate fingerprint features to classify their owner gender. These pooling layers are arranged consecutively up to eight levels. Removing convolution layers makes the process straightforward, and the computation is much faster. This study utilized 200 fingerprint datasets from the NIST (National Institute of Standards and Technology), with male and female fingerprints of 100 samples each. The extracted features were then classified using K-NN (K-Nearest Neighbors) algorithm. The proposed method resulted in an accuracy of 61% to 71.5% or an average of 66.25%.

Random Telegraph Noise-Based True Random Number Generator for Fully Integrated Systems

Generating streams of true random numbers is a critical component of many electronic and information systems. The design of fully integrated, area and power efficient true random number generators (TRNGs) is a challenge. We propose a fully integrated, lightweight implementation that uses the random telegraph noise (RTN) of standard MOSFET as entropy source. It is not analog-intensive, and without traditional post-processing algorithms, the generated random bit sequence passes the National Institute of Standards and Technology (NIST) tests.

Science ranks high in Biden’s 2024 budget plan

Investment in climate science and clean energy technologies made it to the top of President Joe Biden’s priorities in his budget plan for fiscal 2024 , which begins Oct. 1. Basic scientific research, environmental justice, and agricultural innovation also got big nods. The proposal, released March 9, has little chance of getting through the Republican-controlled House of Representatives. But it serves as a starting point for a deeply divided Congress to negotiate spending priorities and cuts over the next several months. Biden’s plan allocates $25 billion, an increase of about $6.5 billion from 2023, for activities authorized by the Creating Helpful Incentives to Produce Semiconductors (CHIPS) and Science Act . That legislation aims to boost the global competitiveness of US research by allowing major increases in funding for the National Science Foundation (NSF), the Department of Energy’s (DOE) Office of Science, and the National Institute of Standards and Technology (NIST).

A Guide to become NIST Compliant

The National Institute of Standards and Technology (NIST) develops cybersecurity standards, guidelines, best practices, and other tools to meet the needs of American business, government organizations, and the general public. Their work spans from giving businesses accurate information that they can utilize immediately to longer-term research that anticipates technology developments and future challenges. Moreover, the needs of American industry and the general public are what drive their cybersecurity endeavors. They collaborate closely with stakeholders to set priorities and ensure that our resources are focused on the most urgent issues they face. NIST also advances the management of privacy risks, some of which are directly connected to cybersecurity, and broadens our understanding of those risks. Among the main areas on which NIST contributes and focuses are cryptography, education and workforce, emerging technologies, risk management, identity and access management, measurements, privacy, trustworthy networks, and trustworthy platforms. This research paper aims to focus on discussing the various controls of the NIST. It also emphasizes on the processes to be followed by the federal agencies to ensure that they are NIST compliant.

Determination of an air kerma-rate correction factor for the S7600 Xoft AxxentⓇ source model

PurposeThe purpose of this work was to provide guidance for the lack of an air-kerma rate standard for the S7600 Xoft Axxent® source by providing a correction factor to apply to the National Institute of Standards and Technology (NIST) traceable S7500 well chamber (WC) calibration coefficient before the development of an S7600 standard at NIST. METHODS AND MATERIALSThe Attix free air chamber (FAC) at the University of Wisconsin Medical Radiation Research Center was used to measure the air-kerma rate at 50 cm for six S7500 and six S7600 sources. These same sources were then measured using five standard imaging HDR1000+ WCs. The measurements made with the FAC were used to calculate source-specific WC calibration coefficients for the S7500 and S7600 source. These results were compared to the NIST traceable calibration coefficients for the S7500 source. The average results for each WC were then averaged together, and a ratio of the S7600 to S7500 WC calibration coefficients was determined. ResultsThe average S7600 air-kerma rate measurement with the FAC was 7% lower than the average air-kerma rate measurements of the S7500 source. On average, the S7500 determined WC calibration coefficients agreed within ±1% of the NIST traceable S7500 values. The S7600 WC calibration coefficients were up to 16% less than the NIST traceable S7500 values. The final correction factor determined to be applied to the NIST traceable S7500 value was 0.8415 with an associated uncertainty of ±8.1% at k = 2. ConclusionsThis work provides a suggested correction factor for the S7600 Xoft Axxent source such that the sources can be accurately implemented in the clinical setting.

GPS-free synchronized pseudo-random number generators for internet-of-things

IntroductionSecuring wireless communications in internet-of-things (IoT) requires both generation and synchronization of random numbers in real-time. However, resource constraints on an IoT device limit the use of computationally intensive random number generators and the use of global positioning systems (GPS) for synchronization. In this paper, we propose a synchronized pseudo-random number generator (SPRNG) that uses a combination of a fast, low-complexity linear-feedback-shift-register (LFSR) based PRNG and a slow but secure, synchronized seed generator based on self-powered timers.MethodsA prototype synchronized self-powered timer (SSPT) array was fabricated in a standard silicon process and was used to generate dynamic random seeds for the LFSR. The SSPTs use quantum-mechanical tunneling of electrons to operate without any external power and are practically secure against tampering, snooping, and side-channel attacks (both power and electromagnetic).ResultsIn this work, we explore protocols to periodically and securely generate random bits using the self-powered timers for seeding the LFSR. We also show that the time-varying random seeds extend and break the LFSR periodic cycles, thus making it difficult for an attacker to predict the random output or the random seed. Using the National Institute of Standards and Technology (NIST) test suite we verify the randomness of the measured seeds from the fabricated ensemble of SSPTs together with the random bit sequences generated by a software-seeded LFSR.DiscussionsIn this modality, the proposed SPRNG could be used as a trusted platform module (TPM) on IoTs and used for verifying and authenticating secure transactions (e.g., software upgrades). Since the SPRNG system does not require access to GPS for synchronization, therefore it could be used in many resource-constrained and adversarial environments.

Overfull: Too Large Aggregate Signatures Based on Lattices

Abstract The Fiat-Shamir with Aborts paradigm of Lyubashevsky has given rise to efficient lattice-based signature schemes. One popular implementation is Dilithium, which has been selected for standardization by the US National Institute of Standards and Technology (NIST). Informally, it can be seen as a lattice analog of the well-known discrete-logarithm-based Schnorr signature. An interesting research question is whether it is possible to combine several unrelated signatures, issued from different signing parties on different messages, into one single aggregated signature. Of course, its size should be significantly smaller than the trivial concatenation of all signatures. Ideally, the aggregation can be done offline by a third party, called public aggregation. Previous works have shown that it is possible to half-aggregate Schnorr signatures, but it was left open if the underlying techniques can be adapted to the lattice setting. In this work, we show that, indeed, we can use similar strategies to obtain a signature scheme allowing for public aggregation whose hardness is proven assuming the intractability of well-studied problems on module lattices. Unfortunately, our scheme produces aggregated signatures that are larger than the trivial solution of concatenating. This is due to peculiarities that seem inherent to lattice-based cryptography. Its motivation is thus mainly pedagogical.

Machine learning for predicting the viscosity of binary liquid mixtures

Viscosity is an important parameter in process engineering and is a key design objective for application areas including the coatings, lubricants, personal care, and pharmaceutical industries. The lack of reliable and general methods for predicting the viscosities of mixtures creates a barrier for modern process engineering and product design. In this work, we developed a graph-based neural network architecture and applied it to the problem of predicting the viscosity of binary liquid mixtures as a function of composition and temperature. To obtain a high-quality training dataset, we also developed an automated curation pipeline and applied it to a large dataset collected from the literature by the National Institute of Standards and Technology (NIST) to be used as training data. The resulting model predicts viscosity with an MAE of 0.043 and an RMSE of 0.080 in log cP units (base 10). To improve the dependability of the model, we developed a classifier that evaluated the reliability of a prediction based on the variance between an ensemble of models. Using this approach, the model had an effective MAE of 0.029 and RMSE of 0.047 for predictions that were assessed as reliable (80% of the test set). Overall, this work provides 1) a large set of curated viscosity data that can be used for future machine learning efforts, 2) a new, graph-based deep learning approach for predicting the viscosity of binary mixtures, and 3) an illustrative case study for how deep learning can be used for accurate and reliable property prediction.

Laser-induced breakdown spectroscopy instrument and spectral analysis for deep-ocean Fe-Mn crusts

IntroductionMarine ferromanganese crusts are potentially important metal resources.The deep-ocean research and survey ships often need to carry out rapid chemical element component analysis of mineral resources, so as to plan for the geological resource exploration mission.MethodsThe laser-induced breakdown spectroscopy can obtain the spectrum of chemical elements by the plasma excited by high-energy laser irradiation on the surface of the sample. A laser induced breakdown spectroscopy optical system for the detection of deepocean ferromanganese crusts is designed and built, which can meet the requirements of near-insitu chemical component detection of deep-ocean mineral resources on ocean-going survey ships.ResultsHyperspectral data of Fe-Mn crusts are carried out by the Laser-induced breakdown spectroscopy (LIBS) system during a deep-sea exploration mission at a depth of 2,490 m in the South China Sea. The experimental parameters of laser energy and spectral acquisition delay are optimized to improve the spectral measurement accuracy. Based on the calibration-free method, the significant spectral features of the chemical elements Fe and Mn were obtained through proper alignment with the National Institute of Standards and Technology (NIST) chemical element spectral library.DiscussionThe LIBS instrument can be placed on board long-range survey vessels in the future to provide a fast, convenient, accurate, and economical detection method for deep-ocean resource exploration.

Efficient GPU Implementations of Post-Quantum Signature XMSS

The National Institute of Standards and Technology (NIST) approved XMSS as part of the post-quantum cryptography (PQC) development effort in 2018. XMSS is currently one of only two standardized PQC algorithms, but its performance limits its use. For example, the fastest record for some standardized parameters still takes more than a minute to generate a keypair. In this article, we present the first GPU implementation for XMSS and its variant XMSS <inline-formula><tex-math notation="LaTeX">$^{\mathsf {MT}}$</tex-math></inline-formula> . The high parallelism of GPUs is especially effective for reducing latency in key generation and improving throughput for signing and verifying. In order to meet various application scenarios, we provide three parallel XMSS schemes: <i>algorithmic parallelism</i> , <i>multi-keypair data parallelism</i> , and <i>single-keypair data parallelism</i> . For these schemes, we design custom parallel strategies that use more than 10,000 cores for all parameters provided by NIST. In addition, we analyze the availability of most previous serial optimizations and explore numerous techniques to fully exploit GPU performance. Our evaluations are made with the XMSSMT-SHA2_20/2_256 parameter set on a GeForce RTX 3090. The result shows the key generation latency is 3.20 ms, a speedup of 21,899× compared to the GPU ported version, which is also 54× speedup faster than the fastest work (174 ms). When 16384 tasks are executed, the throughput (task/s) for signing/verifying in the single-key and multi-key cases is 311,424/415,100 and 145,100/419,887, respectively. Compared to the throughput for signing/verifying (1695/4000) of the fastest work, we obtain a speedup of 184×/104× and 86×/105× in single-key and multi-key cases, respectively.

Can I Really Protect My Broadcast Plant From a Cybersecurity Attack?

Internet Protocol (IP) networks are fundamental building blocks of the broadcast technical plant. Integration with the legacy broadcast infrastructure can range from minimal system control functions to an end-to-end IP-based content transport facility. Regardless of the level of integration, cybersecurity cannot be ignored to ensure a reliable, secure, and protected system. Industry cybersecurity principles are commonly based on a complex framework of principles from the National Institute of Standards and Technology (NIST). The NIST Framework is often a complex and daunting task to implement within a broadcast facility. An effective cybersecurity program begins with the design of the network. This article provides an understanding of practical implementable cybersecurity precautions based on the NIST Framework for the broadcast station. Specific topics to be addressed will include an overall understanding of cybersecurity principles and a step-by-step infrastructure implementation guide for the broadcast facility whether large or small. The guide will be focused on a secure network design approach, the use of Ethernet switch security capabilities, the use of packet filtering and firewalls, and an understanding of implementing common cybersecurity threat mitigation techniques.

A Scoping Review for Cybersecurity in the Construction Industry

The 4th industrial revolution and its inherent digitalization are changing every aspect of the construction industry. However, these technological transformations bring new challenges, including cybersecurity. Although a number of studies in recent years have aimed to analyze cybersecurity issues in the construction sector, further research investment in this area is vital. The first step towards identifying needed and promising research directions in this domain is to systematically analyze the existing body of knowledge and detect knowledge gaps. This study addresses this need through a systematic scoping review designed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Review (PRISMA-ScR). To synthesize the existing knowledge, the extracted information is mapped with multiple benchmarks, including the National Institute of Standards and Technology (NIST) framework for cybersecurity management. The outcomes of the scoping review indicated that, from the construction perspective, the existing literature mainly focuses on a few areas, including Building Information Modeling (BIM), while other digital systems such as construction robots and prefabrication platforms need to be considered in future works. In terms of cybersecurity management, most of the existing studies focus on identifying risks and protecting assets. Other aspects of cybersecurity management, including detecting intrusions, responding to threats, and recovering from cyber-attacks need to be addressed in future studies. Regarding the technology-mediated countermeasures, the existing studies have explored only a limited number of potential solutions with a considerable focus on Blockchain-based systems, while the application of other countermeasures such as network virtualization can be a basis for future studies. Finally, the existing studies focused on procedural guidelines lack systematic solutions for areas including integrated cyber risk management and organizational change.

Determination of Electron Beam Energy in Measuring the Electron-Impact Ionization Cross Section of He-like Fe24+

In an effort to measure electron-impact ionization (EII) cross-sections of He-like Fe24+ at the electron beam ion trap (EBIT) facility of the National Institute of Standards and Technology (NIST), we have experimentally determined the corrections to the nominal beam energy determined by the voltages applied to the EBIT. High-resolution X-ray spectra were recorded at nominal electron beam energies between 6660 eV and 6750 eV using X-ray microcalorimetry based upon an array of 192 transition-edge sensors (TES). A large-scale collisional-radiative simulation of the non-Maxwellian EBIT plasma using relevant atomic data calculated with Flexible Atomic Code allowed us to determine the space-charge correction due to the electron beam including the neutralization factor by the ion cloud of the EBIT.

Securing Commercial Satellites for Military Operations: A Cybersecurity Supply Chain Framework

The increased reliance on commercial satellites for military operations has made it essential for the Department of Defense (DoD) to adopt a supply chain framework to address cybersecurity threats in space. This paper presents a satellite supply chain framework, the Cybersecurity Supply Chain (CSSC) Framework, for the DoD in the evaluation and selection of commercial satellite contracts. The proposed strategy is informed by research on cybersecurity threats to commercial satellites, national security concerns, current DoD policy, and previous cybersecurity frameworks. This paper aims to provide a comprehensive approach for safeguarding commercial satellites used by the DoD and ensuring the security of their supporting components. Inspired by the National Institute of Standards and Technology (NIST) 800-171 requirements and the DoD’s future Cybersecurity Maturity Model Certification (CMMC) process, the two-part framework significantly streamlines the NIST requirements to accommodate small businesses. It also extends key NIST requirements to commercial-off-the-shelf (COTS) suppliers. The CSSC Framework complements the CMMC certification process by addressing the need for cybersecurity requirements for all subcontractors supporting a commercial space asset. The framework incorporates a scoring process similar to CMMC scoring, granting points to a subcontractor for meeting the cybersecurity requirements outlined by the framework. In addition, the framework creates a space architecture overview that details the overall bid score and establishes a matrix based on individual requirements. This model and matrix allow DoD acquisition personnel to closely analyze each contract bid, comparing the subcontractor's strengths and weaknesses to other bidders. The CSSC Framework will allow the DoD to apply NIST standards to subcontractors who do not meet the requirements for CMMC certification.

Chosen ciphertext correlation power analysis on Kyber

The post-quantum cryptography (PQC) standardization process of the National Institute of Standards and Technology (NIST) has entered the final round. Kyber is one of the four key encapsulation mechanism (KEM) finalists. The coefficient multiplication is vulnerable to side-channel attacks. In this paper, we analyzed the multiplication part of Kyber and proposed the methods for constructing ciphertext. By using the chosen ciphertext, more functions can be attacked in the reference implementation of Kyber512. The attacks succeed on the pqm4 implementation with chosen ciphertext while failing with random ciphertext in our experiment environment. For all the attacks, the full secret key recovery can be achieved in a few minutes.

FPGA modeling of a novel fully-synthesizable and secure TRNG based on key-dependent s-box

In this study, the Field Programmable Gate Array (FPGA) implementation of a True Random Number Generator (TRNG) using dynamic key-based s-box architecture as a post-processing technique is presented. In the proposed architecture, the post-processing method of TRNG consists of two different functions, in a total of 32x32 (32-bit input & 32-bit output), containing four independent 8x8 (8-bit input & 8-bit output) s-boxes. Raw random numbers are subjected to three-stage substitution operations in these functions, and their statistical properties are cryptographically improved. The post-processing unit of TRNG is compressionless as the s-boxes are 8 x 8. Thanks to this distinctive feature of the proposed method, TRNG can reach a final output bit rate of 250 Mbps with an entropy of 0.99. With the same output bit rate, TRNG passes the National Institute of Standard and Technology (NIST) Special Publication (SP) 800-22 statistical randomness evaluation tests with success above the minimum confidence interval of 0.9805. In addition to the NIST tests, bias, entropy, correlation, chi-square, and true randomness analyses are also given for TRNG's cryptographic verification. Besides to the statistical requirements, cost and performance analyses for TRNG are also presented in the study. The estimated dynamic power consumption for TRNG needing a low chip area of 2% (3221 LEs) for hardware implementation, is measured as 10.2 mW. The final results show that TRNG has high security and efficiency standards and can be used successfully in embedded cryptographic applications.