National Institute Of Standards And Technology Research Articles

A framework driven by physics-guided machine learning for process-structure-property causal analytics in additive manufacturing

Data analytics with Machine Learning (ML) using physics knowledge and big data offers high potential to continuously transform raw data to newfound knowledge of Process-Structure-Property (PSP) causal relationships. In Additive Manufacturing (AM), however, realizing the potential is still limited largely due to the lack of a systematic way to learn the PSP relationships for various AM processes. To address the limitation, this paper proposes a novel framework driven by physics-guided ML, which consists of three tiers: (1) knowledge of predictive PSP models and physics, (2) PSP features of interest, and (3) raw AM data. The framework defines a PSP-learning process with two sub-processes. The first uses a knowledge-graph-guided top-down approach to generate the requirements for predictive analytics and data acquisition. The second uses a data-driven bottom-up approach to construct and model new PSP knowledge. Together, these processes connect the proposed framework to decision-making and control activities and physical and virtual AM systems, respectively. The paper includes a case study based on Laser Powder Bed Fusion processes including AM Metrology Testbed at the National Institute of Standards and Technology (NIST). The case study introduces predictive ML models and PSP knowledge extracted from the models. We also demonstrate the framework using an ML-Integrated Knowledge Extraction module called MIKE in NIST’s collaborative AM Material Database. The framework newly enables a systematic physics-guided data-driven approach for PSP in AM that can couple physics knowledge with the versatility of data-driven ML models. Using the approach, the framework continuously updates the models (1) to improve the understanding of dynamically generated AM data and (2) to link sub-models into coupled PSP models. Based on the improved understanding, the framework also facilitates decision-making and control activities for AM at multiple scales.

Comparison of Forensic Tool Results on Android Smartphone Backup Files Using NIST Method

Smartphone technology currently developing not only has a positive impact but can also have a negative impact if it is used to commit crimes which can be called cybercrime. Choosing the right forensic tools is very important when conducting an investigation. So it is necessary to research the results of the comparative analysis of the performance of forensic tools on android smartphone backup files. The National Institute of Standards and Technology (NIST) method was used in this study as a parameter and for the digital evidence obtained. The results of the extraction of the OPPO A37f android smartphone from the MOBILedit tools acquired android backup files and the analysis results from using the Magnet AXIOM tools with a data accuracy rate of 39.3% from the predetermined variables. The Oxygen Forensic Tools obtained a data accuracy rate of 28.6% from the variable that has been determined. The Belkasoft Evidence Center tools can get a data accuracy rate of 35.7% of the predetermined variables. The results of this study can be concluded that the Magnet Axiom tool has a high level of accuracy compared to the Oxygen Forensic and Belkasoft Evidence Center tools in extracting data from android smartphone backup files.

Numerical Modeling for Rapid Charging of Hydrogen Gas Vessel in Fuel Cell Vehicle

As a fuel for power generation, high-pressure hydrogen gas is widely used for transportation, and its efficient storage promotes the development of fuel cell vehicles (FCVs). However, as the filling process takes such a short time, the maximum temperature in the storage tank usually undergoes a rapid increase, which has become a thorny problem and poses great technical challenges to the steady operation of hydrogen FCVs. For security reasons, SAE J2601/ISO 15869 regulates a maximum temperature limit of 85 °C in the specifications for refillable hydrogen tanks. In this paper, a two-dimensional axisymmetric and a three-dimensional numerical model for fast charging of Type III, 35 MPa, and 70 MPa hydrogen vehicle cylinders are proposed in order to effectively evaluate the temperature rise within vehicle tanks. A modified standard k-ε turbulence model is utilized to simulate hydrogen gas charging. The equation of state for hydrogen gas is adopted with the thermodynamic properties taken from the National Institute of Standards and Technology (NIST) database, taking into account the impact of hydrogen gas’ compressibility. To validate the numerical model, three groups of hydrogen rapid refueling experimental data are chosen. After a detailed comparison, it is found that the simulated results calculated by the developed numerical model are in good agreement with the experimental results, with average temperature differences at the end time of 2.56 K, 4.08 K, and 4.3 K. The present study provides a foundation for in-depth investigations on the structural mechanics analysis of hydrogen gas vessels during fast refueling and may supply some technical guidance on the design of charging experiments.

한국형 총식이조사 및 UV/태양광 조사 버섯에서의 비타민 D 분석

This study was conducted to evaluate vitamin D intake of Koreans in a total diet study (TDS) and to determine the effect of irradiation on vitamin D synthesis in mushrooms. For analysis, sample were saponified and extracted with hexane, and vitamin D was quantified by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Based on the validation results, the recovery of the National Institute of Standards and Technology (NIST) standard reference sample (SRM) 1849a was 96.7% and the z-score of −1.6 was obtained by the Food Analysis Performance Assessment Scheme (FAPAS) proficiency test (PT) 21115. Vitamin D2 was not detected in any samples, and the highest level of vitamin D3 was detected in mackerel and anchovies ranging from 24.2 to 120.2 μg/kg. The mean daily intake of vitamin D was 0.99 μg/day, as estimated from the vitamin D contents of the analyzed foods and their corresponding intake. The adequate intake (AI) of vitamin D based on the Dietary reference intakes for Koreans provided by the Ministry of Health and Welfare is 5-15 μg/day for Koreans aged 6 to 75 years. Compared with this AI, vitamin D intake of Koreans estimated in this study was inadequate. For that, the increased vitamin D content in ultraviolet (UV)/sun light irradiated mushrooms warrants further research to increase vitamin D intake of Koreans through diet.

Energy Consumption Analysis in Post Quantum Cryptography Using Multivariate Signature Algorithms

Classical cryptographic schemes in use today are based on the difficulty of certain number theoretic problems. Security is guaranteed by the fact that the computational work required to break the core mechanisms of these schemes on a conventional computer is infeasible; however, the difficulty of these problems would not withstand the computational power of a large-scale quantum computer. To this end, the post-quantum cryptography (PQC) standardization process initiated by the National Institute of Standards and Technology (NIST) is well underway. In this paper, the energy consumption of PQC measurements are categorized based on their proposed cryptographic functionality. The results are used in order to identify the most energy-efficient schemes.

A hybrid modified lightweight algorithm for achieving data integrity and confidentiality

<span lang="EN-US">Encryption algorithms aim to make data secure enough to be decrypted by an attacker. This paper combines the Speck and the Salsa20 to make it difficult for an attacker to exploit any weaknesses in these two algorithms and create a new lightweight hybrid algorithm called Speck-Salsa20 algorithm for data integrity and confidentiality (SSDIC). SSDIC uses less energy and has an efficient throughput. It works well in both hardware and software and can handle a variety of explicit plaintext and key sizes. SSDIC solves the difficulties of the Speck algorithm. The sequence generated by Speck is not random and fails to meet an acceptable success rate when tested in statistical tests. It is processed by generating a random key using the Salsa20 algorithm. Salsa20 is a high-speed secure algorithm that is faster than advanced encryption standard (AES) and can be used on devices with low resources. It uses a 256-bit key hash function. The recovery of the right half of the original key of the Speck algorithm is also handled by modifying the Speck round function and the key schedule. Simulation results show, according to a National Institute of Standards and Technology (NIST) test, the performance achieved by the SSDIC is increased by nearly 66% more than that achieved from the Speck in terms of data integrity and confidentiality.</span>

A High-Speed FPGA-Based True Random Number Generator Using Metastability With Clock Managers

True random number generators (TRNGs) are fundamentals in many important security applications. Though they exploit randomness sources that are typical of the analog domain, digital-based solutions are strongly required especially when they have to be implemented on Field Programmable Gate Array (FPGA)-based digital systems. This brief describes a novel methodology to easily design a TRNG on FPGA devices. It exploits the runtime capability of the Digital Clock Manager (DCM) hardware primitives to tune the phase shift between two clock signals. The presented auto-tuning strategy automatically sets the phase difference of two clock signals in order to force on one or more flip-flops (FFs) to enter the metastability region, used as a randomness source. Moreover, a novel use of the fast carry-chain hardware primitive is proposed to further increase the randomness of the generated bits. Finally, an effective on-chip post-processing scheme that does not reduce the TRNG throughput is described. The proposed TRNG architecture has been implemented on the Xilinx Zynq XC7Z020 System on Chip (SoC). It passed all the National Institute of Standards and Technology (NIST) SP 800–22 statistical tests with a maximum throughput of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$300 \times 10^{6}$ </tex-math></inline-formula> bit per second. The latter is considerably higher than the throughput of other previously published DCM-based TRNGs.

Working with cryptographic key information

It is important to create a cryptographic system such that the encryption system does not depend on the secret storage of the algorithm that is part of it, but only on the private key that is kept secret. In practice, key management is a separate area of cryptography, which is considered a problematic area. This paper describes the main characteristics of working with cryptographic key information. In that, the formation of keys and working with cryptographic key information are stored on external media. The random-number generator for generating random numbers used for cryptographic key generation is elucidated. To initialize the sensor, a source of external entropy, mechanism “Electronic Roulette” (biological random number), is used. The generated random bits were checked on the basis of National Institute of Standards and Technology (NIST) statistical tests. As a result of the survey, the sequence of random bits was obtained from the tests at a value of P≥0.01. The value of P is between 0 and 1, and the closer the value of P is to 1, the more random the sequence of bits is generated. This means that random bits that are generated based on the proposed algorithm can be used in cryptography to generate crypto-resistant keys.

A cyber resilience analysis case study of an industrial operational technology environment

Cyber resilience is an active research area offering a novel approach to Cyber Security. The term appeared due to the concerning number of cyber-attacks on critical infrastructure. The National Institute of Standards and Technology (NIST) developed a framework to assist organisations with techniques and approaches to improving cyber resilience. However, there are a sparsity of case studies that speak to the adoption or measurement of these novel approaches within a complex industrial control environment. This paper presents a case study analysis of a manufacturing plant assessment drawing on key themes from the NIST literature. The paper presents how well NIST constructs can be adopted to find cyber-resilient enhancement opportunities and to decide if an evaluation of the results could supply a quantitative baseline measure of an organisation’s overall resilience. Conclusions drawn show that although the framework did partially aid with the analysis process, the frameworks ease of adoption assume an organisation has a conventional cyber security foundation; NIST should make this clear within their guidance. Furthermore, the accompanying evaluation process was not sufficient to quantitatively measure the overall cyber resilience maturity for this case study.

A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting.

The development of reinforced polymer composite materials has had a significant influence on the challenging problem of shielding against high-energy photons, particularly X-rays and γ-rays in industrial and healthcare facilities. Heavy materials' shielding characteristics hold a lot of potential for bolstering concrete chunks. The mass attenuation coefficient is the main physical factor that is utilized to measure the narrow beam γ-ray attenuation of various combinations of magnetite and mineral powders with concrete. Data-driven machine learning approaches can be investigated to assess the gamma-ray shielding behavior of composites as an alternative to theoretical calculations, which are often time- and resource-intensive during workbench testing. We developed a dataset using magnetite and seventeen mineral powder combinations at different densities and water/cement ratios, exposed to photon energy ranging from 1 to 1006 kiloelectronvolt (KeV). The National Institute of Standards and Technology (NIST) photon cross-section database and software methodology (XCOM) was used to compute the concrete's γ-ray shielding characteristics (LAC). The XCOM-calculated LACs and seventeen mineral powders were exploited using a range of machine learning (ML) regressors. The goal was to investigate whether the available dataset and XCOM-simulated LAC can be replicated using ML techniques in a data-driven approach. The minimum absolute error (MAE), root mean square error (RMSE), and R2score were employed to assess the performance of our proposed ML models, specifically a support vector machine (SVM), 1d-convolutional neural network (CNN), multi-Layer perceptrons (MLP), linear regressor, decision tree, hierarchical extreme machine learning (HELM), extreme learning machine (ELM), and random forest networks. Comparative results showed that our proposed HELM architecture outperformed state-of-the-art SVM, decision tree, polynomial regressor, random forest, MLP, CNN, and conventional ELM models. Stepwise regression and correlation analysis were further used to evaluate the forecasting capability of ML techniques compared to the benchmark XCOM approach. According to the statistical analysis, the HELM model showed strong consistency between XCOM and predicted LAC values. Additionally, the HELM model performed better in terms of accuracy than the other models used in this study, yielding the highest R2score and the lowest MAE and RMSE.

Design and Implementation of a flexible Multi-purpose Cryptographic System on low cost FPGA

The design of cryptographic hardware that supports multiple cryptographic primitives is common in literature. In this work, a new design is presented consisting of a multi-purpose cryptographic system featuring both 128-bit pipelined AES-CORE (Advanced Encryption Standard) for high-speed symmetric encryption and a Keccak hash core on a low-cost FPGA. The KECCAK-CORE’s security and performance parameters are tunable in the sense that capacity, bitrate, and the number of rounds can be user-defined. Such flexibility enables the core to suit a large range of security requirements. The structure of Keccak’s sponge construction is exploited to enable different modes of operation. An example application outlined in this work is Pseudo Random Number Generation (PRNG). With few adjustments, the KECCAK-CORE was also operated as a post-processing unit for True Random Number Generation (TRNG) that uses the analog Lorenz chaotic circuit as a physical entropy source. The multi-purpose design was implemented in VHDL targeting an IntelFPGA Cyclone-V FPGA. For AES symmetric encryption, a maximum throughput of 31.1Gbps was achieved and a logic usage of 25146LEs (23% of the FPGA) in the case of the pipelined variant of AES-CORE. For the KECCAK-CORE, maximum throughput figures of 5.81, 8.4, and 11Gbps were achieved for the three SHA-3 variants 512, 384, and 256-bit respectively, with an area usage of 8947LEs (8%). The system as a whole occupies an area of 26909LEs (26%). The random sequences generated by the system operating in PRNG and TRNG post- processing modes successfully passed the National Institute of Standards and Technology (NIST) statistical test suite (NIST SP 800-22). The information entropy analysis performed on the post-processed TRNG sequences indicates an average of 0.935.

Model-Based Systems Engineering Cybersecurity for Space Systems

As industries in various sectors increasingly adopt model-based systems engineering (MBSE) for system lifecycle design and development, engineers can manage and describe systems of higher complexity than ever before. This is especially true for the field of space systems; while past missions have developed using document-based planning, it is only in the last several years that NASA and other organizations in the space industry have begun using MBSE. One crucial factor of space systems development that is often overlooked is cybersecurity. As space systems become more complex and cyberphysical in nature, cybersecurity requirements become more difficult to capture, especially through document-based methods; a need for a means by which to continuously verify and validate systems cybersecurity for cyberphysical space missions arises. By expanding upon a National Institute of Standards and Technology (NIST) framework for cyber resiliency, this work proposes a methodology that uses MBSE traceability functionality to demonstrate adequate cybersecurity for cyberphysical space systems using SysML requirements modeling capabilities. Key goals, objectives, and strategic principles leading to achieving cybersecurity at all levels of the system’s architectural hierarchy are presented. Recommendations for the future of space cybersecurity include the addition of the space sector to the Department of Homeland Security Cybersecurity &amp; Infrastructure Security Agency’s list of critical infrastructure sectors to improve standardization and control of space cyberinfrastructure.

Optimization of Random Telegraph Noise Characteristics in Memristor for True Random Number Generator

Memristor devices can be utilized for various computing applications, and stochastic computing is one of them. The intrinsic stochastic characteristics of the memristor cause unpredictable current fluctuations by the capture and emission of electrons in a trap site. Herein, a true random number generator (TRNG) using the random telegraph noise (RTN) of the memristor as an entropy source is proposed. TiOx/Al2O3memristors are fabricated, and the capture time probability of the RTN characteristics is modulated to 50% with varying read‐voltage and device conductance state. In addition, the TRNG operations with the RTN current signals as entropy sources are experimentally demonstrated with a customized breadboard, and the randomness is verified with the National Institute of Standards and Technology (NIST) tests.

Confined phase behavior of ethane in nanoporous media: An experimental investigation probing the effects of pore size and temperature

Ethane is rapidly becoming an efficient and dependable clean energy source for fast-growing and developing countries. It is the second most abundant natural gas after methane. However, it poses a major problem for ozone pollution and plays a significant role in greenhouse warming once released into the atmosphere. Therefore, understanding the mechanisms that govern its behavior during storage in natural and artificial nanoporous materials is essential for numerous industrial and environmental applications. In this work, the confined phase behavior of ethane was investigated in ordered mesoporous silica material MCM-41 at varying nanoscale-pore sizes and temperatures. Adsorption and desorption isotherms were experimentally measured for a wide range of nanopore diameters (7, 10.2, 11.3, and 12.3 nm) and temperatures (varying from −65 to −20 °C) using an automated gravimetric nanocondensation apparatus. This system enabled direct quantification of the mass of ethane adsorbed onto the surfaces of nanopores. We examined the impact of the pore diameter and temperature on the adsorption, capillary condensation, and evaporation of ethane in nanoporous media. The capillary condensation and evaporation pressures were determined using the Lorentzian functions. The accuracy of the measurements was confirmed by comparing the experimental bulk condensation pressures with those reported by the National Institute of Standards and Technology (NIST).The results demonstrate that the capillary condensation pressures increased with ascending pore diameters and temperatures. They also indicate that the degree of suppression of the saturation pressure due to confinement is predominant at low temperatures. The percent reduction in the pressure of vapor-liquid phase change decreased with an increase in temperature. A similar trend was observed with respect to changes in the pore size. The results showed that the effect of confinement was weakened as the nanopores became wider. Furthermore, insights were developed about the effects of pore diameter and temperature on the occurrence of the supercritical-like behavior of ethane in nanopores. A good agreement was evident between our results and the examples available in the literature.To the best of our knowledge, we present the first experimental study that describes the confined phase behavior of ethane using a patented gravimetric apparatus. This work presents a systematic approach to understand the effects of confinement in nanoporous media. Furthermore, it can aid the development of new ethane storage applications, especially the characterization of natural and artificial porous materials for energy and environment-related solutions.

HASIL ANALISIS STATISTIK, DIFERENSIAL, DAN KUALITAS CITRA TERHADAP KOMPOSISI LOGISTIC CIRCLE MAP

The problem of data security is still a matter of concern in the digital era like today. An effective security method is needed and it is difficult to break into. Encryption is an effective method of ensuring data security. The encryption algorithm is built using a chaotic cipher base so that performance in securing data and information increases. The new chaotic composition resulting from two chaotic maps will have better randomness. Logistic Map and Circle Map were chosen because they have good randomness. The new chaotic composition is called the Logistic Circle Map (LC Map). By bifurcation diagram test, Lyapunov Exponent, and NIST random test, the best density occurs at X_0=0.9 , K = 1000, r = 3.7 and Ω = 0.4. The new chaotic composition parameters have passed all 16 NIST (National Institute of Standards and Technology) tests. There are four parameters used in this study in order to obtain a sufficiently high key space, namely 1.296 ×〖 10〗^84 combinations and having a high level of lock sensitivity of 10−17. The image encryption algorithm of the LC Map function has high resistance against various attacks. This can be proven by carrying out key space tests, sensitivity tests for key spaces, histogram tests, entropy, correlation coefficients, and differential tests using the UACI NPCR. The test results on digital image decryption using the Mean Square Error (MSE) show a result of 0 and the Peak Signal to Noise Ratio (PSNR) shows a result of ∞. That is, the encrypted image is similar to the original image.

A Comprehensive Review on Smart Grid Ecosystem

A smart grid is an intervention technology for the massive energy demand of the world today. It combines cyber-physical technologies, information communication technology, and electrical power networks from the generating company stations to the end-users while ensuring bidirectional communication among the actors. The smart grid is a complex growing technology that is yet to reach its maturity state. This paper seeks to examine the literature on the state of the art of smart grid technology both from the industry perspective and from academia. To this end, a literature review with a qualitative deductive approach built on the National Institute of Standards and Technology (NIST) guideline and the simplified International Telecommunication Union Telecommunication Standardization Sector (ITU-T) five-domain model were used as a guide to this research. Furthermore, the paper reviewed Smart Grid data centre topologies and identified prospects in spine-leaf architecture as a promising architecture that can be adapted in a smart grid ecosystem data centre design. The literature was searched from the databases: IEEE Xplore Digital Library, Springer Link Digital Library, and Google Scholar, IET Digital Library, Frontiers Library, ACM Digital Library repositories resulting in 151 papers after several exclusions. The work reviewed relevant literatures published from 2002 to 2021 and grouped the reviewed papers according to the key domains of the NIST/ITU-T model. Based on the evaluated literature, the need for more built-in predictive learning curves in smart grid systems and robust Smart grid architecture with enhanced data centre design for Smart grid systems is observed and recommended Keywords: Smart Grid, Smart Metre, Data Centre Computing, Distributed Energy, Protocols

Risk Management Framework Analysis

Risk management is widely regarded as one of the most effective methods for preventing the occurrence, avoiding, or limiting the impact of risks through a systematic, structured approach. Therefore, it helps organizations achieve their desired goals with the fewest losses. While technology advances on a daily basis, cyber threats grow at an exponential rate. As a result, cyber risk has become an important field to manage in order to assist organizations in achieving their goals in terms of cyber security. In this study, we present the most popular and common risk management frameworks: the International Standard Organization ISO (ISO 31000:2018), the National Institute of Standards and Technology (NIST), and the Committee of Sponsoring Organizations of the Treadway Commission (COSO), which will help the organizations handle the cyber risk. We review their structures, principles, and processes and how they are working to analyze, assess, and manage risk. Also, how to apply the risk management framework in the context of cybercrime. Finally, we discuss the features and limitations of each of them in terms of applicability, orientations, similarities, and contrasts.

Gas Chromatography-Mass Spectrometry (GC-MS) Metabolite Profiling of Citrus limon (L.) Osbeck Juice Extract Evaluated for its Antimicrobial Activity Against Streptococcus mutans.

Purpose The present study aimed to determine the antimicrobial nature of Citrus limon juice extract against Streptococcus mutans and to identify its metabolic profile by gas chromatography-mass spectrometry (GC-MS) technique. Materials and methods The cariogenic bacteria S. mutans were procured from Microbial Type Culture Collection and Gene Bank (MTCC), Chandigarh, India, and revived on brain heart infusion (BHI) agar. The C. limon (L.) Osbeck fruits were authenticated from the University of Trans-Disciplinary Health Sciences and Technology (TDU), Bengaluru, India. The antibacterial property of lyophilized lemon juice extract (LJE) dissolved in methanol was evaluated against S. mutans (MTCC 497) by the agar well diffusion assay. GC-MS technique was employed to identify the volatile metabolite profile of the methanolic LJE sample. The metabolite masses of the respective compounds were identified using the National Institute of Standards and Technology (NIST) library. Results The methanolic LJE sample concentration from 5 to 25 mg/ml did not demonstrate antimicrobial activity, while 30 to 100 mg/ml displayed antibacterial activity against S. mutans. Chlorohexidine (100 µg/ml) was used as the positive control, while methanol was used as the negative control. Significant antimicrobial metabolites were detected in the methanolic LJE sample by GC-MS analysis. Maleic anhydride, succinic anhydride, 6-Oxa-bicyclo[3.1.0] hexan-3-one, and 3-methyl-2,5-Furandione were the key metabolites identified in the methanolic LJE sample. Conclusion The present study reports that C. limon is a potential candidate for the pharmaceutical industry as it possesses bioactive compounds demonstrating therapeutic properties. Further investigations are warranted to determine the individual and synergetic effects of identified metabolites in the methanolic LJE sample for its antimicrobial property. Special attention needs to be focussed on translational research for the development of anti-caries products from C. limon.

SIM Thermocouple Type S Supplementary Comparison

Main textA collapsed star type S thermocouple intercomparison was performed over the International Temperature Scale of 1990 (ITS-90) temperature range from 0 °C to 1100 °C. This was an Inter-American Metrology System (SIM) regional intercomparison piloted by the National Institute of Standards and Technology (NIST). Eleven laboratories (including NIST) participated in the intercomparison. Twenty-one type S thermocouples were constructed and calibrated at NIST, of which ten served as transfer standards. The thermocouples were identified as Cut 1 through Cut 21. Each thermocouple was calibrated by the metal fixed-point method at the freezing points of Zn, Al, Ag, and Au. The 21 calibrations were ultimately used to determine the reference values (RV) for the intercomparison. Subsequently the artifacts were calibrated at a participating laboratory by comparison with a local standard and/or by fixed-point method. Subsequently they were returned to the pilot laboratory where they were remeasured at the freezing point of silver (for purposes of determining a transfer uncertainty). Although thermocouples are not a standard interpolating instrument on the ITS-90, they are proposed as an approximation technique and are a widely used thermometer; so, it is useful to look at the measurement capabilities involved in their calibration.To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.The final report has been peer-reviewed and approved for publication by the CCT, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Bit Flipping Key Encapsulation for the Post-Quantum Era

It is a matter of time before quantum computers will break the cryptosystems like RSA and ECC underpinning today’s internet protocols. As Post-Quantum Cryptography (PQC) is a low-cost approach compared to others like quantum key distribution, the National Institute of Standards and Technology (NIST) has recently reviewed and analyzed numerous approaches to PQC. As a PQC candidate, Bit Flipping Key Encapsulation (BIKE) is expected to be standardized as a general-purpose Key Encapsulation Mechanism (KEM) by NIST. However, it lacks a comprehensive review of BIKE associated with technical analysis. This paper aims to present an in-depth review and analysis of the BIKE scheme with respect to relevant attacks. We provide a comprehensive review of the original McEliece (ME) scheme and present a detailed discussion on its practical challenges. Furthermore, we provide an in-depth study on the challenges of ME and BIKE cryptosystems in achieving the Indistinguishability under Chosen-Ciphertext Attack (IND-CCA) security. We provide an analysis of these cryptosystems and their security against several attacks before pointing out the research gaps for strengthening BIKE.