Finding Collisions against 4-Round SHA-3-384 in Practical Time

ABSTRACTThe National Institute of Standards and Technology (NIST) has developed a dynamic and on-going educational outreach program designed to support middle school science teachers and increase their understanding of the science they teach with applications to the real world and connections to the latest NIST research. In the NIST Summer Institute for Middle School Science Teachers, science topics are taken from NIST research pertinent to the middle school curriculum, and the research is translated for use in the classroom. During the two-week summer program teachers from around the country are given the opportunity to focus on NIST research as it relates to the middle school classroom by participating in a combination of hands-on activities, lectures, tours, and visits with scientists and engineers in their laboratories. The NIST Summer Institute is designed to increase teacher understanding of the subjects they teach, provide inquiry activities for the classroom, rekindle teachers’ enthusiasm for science, provide increased understanding of how scientific research is performed, create a learning community of teachers and scientists, and provide role models for the teachers. Teachers finish the NIST Summer Institute with a wealth of knowledge about core topics in introductory biology, chemistry, physics, and materials to integrate these topics into their existing curriculum.The NIST Summer Institute has spawned additional related outreach activities, including “Science Afternoons at NIST,” in which teachers are invited back to NIST during the school year for events in which the focus is on a single topic such as designing buildings to resist earthquakes, infrared energy, and nanomagnetism. Based on continued requests from participants in the NIST Summer Institute, an additional program, the NIST Research Experience for Teachers program, was begun in 2011 with teachers performing research at NIST under the guidance of NIST scientists and engineers, and designing ways to take their research experience back into the classroom to share with their students. This proceeding will give examples of topics covered and activities developed in past Summer Institutes, as well as ways similar Institutes are being implemented at other locations. While not a teaching institution but a research institute focused on meeting the measurement science needs of the nation, NIST has a wealth of resources for the education community. The NIST Summer Institute for Middle School Science Teachers is one way of sharing these resources and building partnerships between middle school science teachers and their students and NIST scientists and engineers.

The National Institute of Standards and Technology (NIST) is the National Measurement Institute (NMI) for the US. All dosimetric measurements made in American radiotherapy clinics should be traceable to the primary standards maintained by NIST. The accuracy of the NIST standards, and traceability to the Systeme Internationale (SI), is ensured through the Bureau International des Poids et Mesures (BIPM), the international laboratory that co‐ordinates comparisons between NIST and other NMIs around the world (such as the National Research Council Canada). A continuous calibration chain, therefore, links the measurement of dose in the clinic to the internationally agreed‐upon definition of the gray, an essential requirement in ensuring equivalence of clinical dose delivery irrespective of location. Within the US, traceability of radiationdose measurements to the SI is ensured through activities of the Radiation Interactions and Dosimetry (RID) Group at NIST, whose primary mission is to develop, maintain, and disseminate the national measurement standards for the dosimetry of x rays,gamma rays, electrons, and other charged particles. In the case of medical dosimetry, relevant standards are disseminated both directly to the customer and through the AAPM Accredited DosimetryCalibration Laboratory (ADCL) network by means of calibrations and proficiency testing services, provided to maintain measurement‐quality assurance and traceability. The evolving measurement needs of industry, medicine and government provide impetus for the improvement of existing standards and the development of new standards. Research activities in support of this part of the RID Group's mission address a variety of topics in fundamental and applied radiation physics. These efforts are driven partly by advancements in instrumentation technology and partly by the ever expanding domain of measurement standards made possible by such advancements. The widespread adoption of conformal beam therapies, for example, has driven the standards community to develop new approaches for standard reference dosimetry of “nonstandard” beams. At NIST, this has spurred a research program in water calorimetry that is looking into ultrasonic time‐of‐flight approaches to imagingdose in water. Ultimately, this or similar approaches might lead to new ways of imaging complicated dose distributions in tissue as well as give the standards community new tools for reference dosimetry of present and future beam technologies. In this session, attendees will learn how the accuracy of their clinical measurements is assured as a result of comparisons between NIST and other NMIs around the world as well as NIST proficiency tests and AAPM accreditation of the ADCLs. It will be shown how NIST staff members are active within critical AAPM scientific committees so that measurement needs in the clinic can be addressed by the standards laboratory, resulting in the development of new standards and/or methodologies. Learning Objectives: 1. Understand the impact of measurement standards in general, and in particular the work of primary standards laboratories such as NIST, on clinical radiationdosimetry. 2. Understand the calibration chain from primary standards laboratory to radiotherapy clinic. 3. Understand how NIST interacts with various AAPM committees to ensure that the measurement needs of the user community are met.

Identification and application of security measures for petrochemical industrial control systems

The National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC) requires accurate gas mixtures containing argon (Ar), helium (He), hydrogen (H(2)), and oxygen (O(2)) in a balance of nitrogen (N(2)) to calibrate mass spectrometer-based sensors used around their manned and unmanned space vehicles. This also includes space shuttle monitoring around the launch area and inside the shuttle cabin. NASA was in need of these gas mixtures to ensure the safety of the shuttle cabin and the launch system. In 1993, the National Institute of Standards and Technology (NIST) was contracted by NASA to develop a suite of primary standard mixtures (PSMs) containing helium, hydrogen, argon, and oxygen in a balance gas of nitrogen. NIST proceeded to develop a suite of 20 new gravimetric primary PSMs. At the same time NIST contracted Scott Specialty Gases (Plumsteadville, PA) to prepare 18 cylinder gas mixtures which were then sent to NIST. NIST used their newly prepared PSMs to assign concentration values ranging from 100 to 10,000 micromol/mol with relative expanded uncertainties (95% confidence interval) of 0.8-10% to the 18 Scott Specialty Gases prepared mixtures. A total of 12 of the mixtures were sent to NASA as NIST traceable standards for calibration of their mass spectrometers. The remaining 6 AIRGAS mixtures were retained at NIST. In 2006, these original 12 gas standards at NASA had become low in pressure and additionally NASA needed a lower concentration level; therefore, NIST was contracted to certify three new sets of gas standards. NIST prepared a new suite of 22 PSMs with weighing uncertainties of <0.1%. These 22 PSMs were compared to some of the original 20 PSMs developed in 1993 and with the NIST valued assigned Scott Specialty Gas mixtures that NIST had retained. Results between the two suites of primary standards and the 1993 NASA mixtures agreed, verifying their stability. At the same time, NASA contracted AIRGAS (Chicago, Illinois) to prepare 45 cylinder gas mixtures which were then sent to NIST. Each of the 3 sets of standards contained 15 cylinder gas mixtures: set no. 1, He at 12,000 micromol/mol, H(2) at 600 micromol/mol, Ar at 100 micromol/mol, and O(2) at 600 micromol/mol; set no. 2, He at 15 000 micromol/mol, H(2) at 5000 micromol/mol, Ar at 1000 micromol/mol, O(2) at 5000 micromol/mol; and set no. 3, He at 50 micromol/mol, H(2), Ar, and O(2) each at 25 micromol/mol with a balance gas of N(2). NIST used their newly prepared primary standards to assign concentration values to each component in these three new mixture sets to relative expanded uncertainties of 0.5-2.2%. The NIST certified AIRGAS prepared mixtures were then sent to NASA to use as "working standards" to calibrate their mass spectrometers (MSs).

—Recently, a fast and secure hash function SFHA – 256 has been proposed and claimed as more secure and as having a better performance than the SHA – 256. In this paper an improved version of SFHA – 256 is proposed and analyzed using two parameters, namely the avalanche effect and uniform deviation. The experimental results and further analysis ensures the performance of the newly proposed and improved SFHA-256. From the analysis it can be concluded that the newly proposed algorithm is more secure, efficient, and practical. Keywords —SHA-256, SFHA-256, Improved SFHA-256 1. I NTRODUCTION The hash function H accepts the variable-sized message M as input and outputs a fixed-size representation H(M) of M, which is sometimes called a message digest [1]. I.B. Damgard et.el., discussed the construction of hash functions and presented an efficient and much more secure scheme with the combination of RSA system with the collision free hash function based on fac-toring [2]. Hash functions for message authentications are proposed in [3]. A universal one-way hash function family is discussed in [4]. SHA-1 is a cryptographic hash function published by the National Institute of Standards and Technology (NIST). The three SHA algorithms are SHA-0, SHA-1, and SHA-2. The SHA-0 algorithm was not used in many applications. On the other hand, SHA-2 differs from the SHA-1 hash function. SHA-1 is the most widely used hash function. Several widely-used security ap-plications and protocols are based on SHA-1. In 2005, security flaws were identified in SHA-1 [5]. A prime motivation for the publication of the Secure Hash Algorithm was the Digital Signa-ture Standard. The Digital Signature Algorithm (DSA) is a United States Federal Government standard or FIPS for digital signatures. It was proposed by the National Institute of Standards and Technology (NIST) in August 1991 for use in their Digital Signature Standard (DSS). The ElGamal signature scheme is a digital signature scheme that is based on the difficulty of com-puting discrete logarithms. It was described by Taher ElGamal in 1984 [6]. The Elliptic Curve Digital Signature Algorithm (ECDSA) is a variant of the Digital Signature Algorithm (DSA) that uses Elliptic curve cryptography [7, 8]. Recently, Hassan. M. Elkamchouchi et el., proposed a fast and secure hash function (SFHA -

There has been a long partnership in the materials science of building materials between the National Institute of Standards and Technology (NIST) in the United States and the International Union of Laboratories and Experts in Construction Materials, Systems and Structures (RILEM). This paper discusses on the technical contributions NIST has made to RILEM, focusing on the articles published in Materials and Structures, whose 50-year anniversary is being celebrated in this issue. Since 1968, NIST has had a name change and a building materials division was formed, merged, and renamed since the 1970s, while RILEM has stayed constant in its name and organization, although its technical committee structure is purposely fluid. Many NIST personnel have contributed to the partnership between RILEM and NIST in more than one material type. This overview briefly covers these areas.

Various new light-emitting diodes (LEDs) including white LEDs are being actively developed for solid-state lighting and many other applications, and there are great needs for accurate measurement of various optical quantities of LEDs. Traditional lamp standards do not suffice for specific measurement needs for LEDs. The National Institute of Standards and Technology (NIST) has recently established calibration services for photometric quantities (luminous intensity and luminous flux) of LEDs, but the measurement needs are expanding. This paper covers the current capabilities and services NIST provides for calibration of LEDs and discusses the future needs for optical metrology of LEDs. Work is just completed at NIST to provide official color calibrations of LEDs (chromaticity coordinates, peak wavelength, correlated color temperature, etc.). Another urgent need addressed is radiometric calibration of LEDs, particularly the total radiant flux (watt) of ultraviolet (UV) LEDs used to excite phosphors for white LEDs. Also, as spectroradiometers coupled with an integrating sphere are increasingly used total spectral radiant flux standards from NIST are in urgent demand. Presented is the scope of NIST plans to realize these new radiometric calibration capabilities for LEDs in the near future.

Standards for bullets and casings

The efficiency of extraction of polycyclic aromatic hydrocarbons (PAHs) with molecular masses of 252, 276, 278, 300, and 302 Da from standard reference material diesel particulate matter (SRM 2975) has been investigated using accelerated solvent extraction (ASE) with dichloromethane, toluene, methanol, and mixtures of toluene and methanol. Extraction of SRM 2975 using toluene/methanol (9:1, v/v) at maximum instrumental settings (200 °C, 20.7 MPa, and five extraction cycles) with 30-min extraction times resulted in the following elevations of the measured concentration when compared with the certified and reference concentrations reported by the National Institute of Standards and Technology (NIST): benzo[b]fluoranthene, 46%; benzo[k]fluoranthene, 137%; benzo[e]pyrene, 103%; benzo[a]pyrene, 1,570%; perylene, 37%; indeno[1,2,3-cd]pyrene, 41%; benzo[ghi]perylene, 163%; and coronene, 361%. The concentrations of the following PAHs were comparable to the reference values assigned by NIST: indeno[1,2,3-cd]fluoranthene, dibenz[a,h]anthracene, and picene. The measured concentration of dibenzo[a,e]-pyrene was lower than the information value reported by the NIST. The measured concentrations of other highly carcinogenic PAHs (dibenzo[a,l]pyrene, dibenzo[a,i]pyrene, and dibenzo[a,h]pyrene) in SRM 2975 are also reported. Comparison of measurements using the optimized ASE method and using similar conditions to those applied by the NIST for the assignment of PAH concentrations in SRM 2975 indicated that the higher values obtained in the present study were associated with more complete extraction of PAHs from the diesel particulate material. Re-extraction of the particulate samples demonstrated that the deuterated internal standards were more readily recovered than the native PAHs, which may explain the lower values reported by the NIST. The analytical results obtained in the study demonstrated that the efficient extraction of PAHs from SRM 2975 is a critical requirement for the accurate determination of PAHs with high molecular masses in this standard reference material and that the optimization of extraction conditions is essential to avoid underestimation of the PAH concentrations. The requirement is especially relevant to the human carcinogen benzo[a]pyrene, which is commonly used as an indicator of the carcinogenic risk presented by PAH mixtures.

Recent U.S. Food and Drug Administration (FDA) guidance recognizes that today’s medical devices face a host of cyberthreats. Medical device manufacturers, in turn, face the need to assess and mitigate cyber risks. By combining the cyber risk framework of the National Institute of Standards and Technology (NIST) with the existing International Organization for Standardization (ISO) 14971 Safety Risk Management (SRM) process, manufacturers can leverage proven best practices to make their devices safer and more effective. The cyberthreat to medical devices is based on two factors. First, increasingly faster and more efficient processors now enable full operating systems to run on small implant devices. Previously, only dedicated firmware could have been used. Second, modern hardware can readily connect to networks using wired and wireless protocols. Both factors offer markedly increased capability for patients, physicians, caregivers, and healthcare technology management (HTM) professionals, at the cost of opening unforeseen and unintended doorways into a device. Opening unintended doorways can compromise medical devices in three major areas of cybersecurity: confidentiality, integrity, and availability. Confidentiality refers to preserving authorized restrictions on information access and disclosure, including means for protecting patient privacy and corporate proprietary information. Integrity means guarding against improper information modification or destruction and includes ensuring information nonrepudiation and authenticity. Availability is ensuring timely and reliable access to and use of information. As embedded medical devices grow in complexity and ability, an end-to-end cybersecurity framework is needed to ensure that they achieve the confidentiality, integrity, and availability required for successful operation. Cybersecurity concerns have factored into medical device design for some time, but additional attention has been focused on the topic by recent FDA communications, including a recent guidance document and a safety communication. These documents, however, lack clear instructions on what needs to be considered and tested—a comprehensive standard could be years away. To ensure safety and effectiveness and reduce exposure to liability, device manufacturers need to be proactive in defining and applying cybersecurity controls for their medical devices. The problem facing medical device development teams is complex; it involves securing a device against an ever-growing number of cybersecurity threats while balancing usability, performance, and safety. A viable approach Applying Cyber Risk Management To Medical Device Design

Cybercrime is a criminal act that utilizes technology, from devices to internet networks. The purpose of cybercrime cases is to harm others by committing theft, hacking, fraud, spreading viruses, and other digital crimes. In every cybercrime case there are usually traces of activity left behind, in the form of traces of activity (history) related can be used as evidence, both in the form of electronic evidence (in the form of electronic physical devices or storage media) and digital evidence (such as document files, history files, or log files containing relevant data). The National Institute of Standards and Technology (NIST) method is a method that is often used in digital forensics to overcome cybercrime cases. The National Institute of Standards and Technology (NIST) method is a method that aims for investigations in finding related information, in order to provide structured information, and process the information obtained. NIST refers to general principles such as collection, examination, analysis, reporting. Using the NIST (National Institute of Standards and Technology) method, the process at each stage is Data Collection is the process of collecting user data and face images through an easy-to-use user interface, Examination is the stage of processing images to detect faces using the Haar Cascade algorithm, Analysis is the process of training a face recognition model (LBPH) and applying it to recognize faces in images or videos. Reporting is the stage of displaying face recognition results and related information to the user through the GUI.

Detecting tattoo images stored in information technology (IT) devices of suspects is an important but challenging task for law enforcement agencies. Recently, the U.S. National Institute of Standards and Technology (NIST) held a challenge and released a tattoo database for the commercial and academic community in advancing research and development into automated image-based tattoo recognition technology. The best tattoo detection result in the NIST challenge was achieved by MorphoTrak with accuracy of 96.3%. This paper aims to answer three questions. 1) Is the NIST database suitable for training algorithms to detect tattoo images stored in IT devices of suspects? 2) Can convolutional neural networks (CNNs) outperform the MorphoTrak's algorithm? 3) How do training databases impact on tattoo detection performance? The NIST tattoo detection database containing 2,349 images and a database containing 10,000 collected from Flickr are utilized to answer these questions. The Flickr images taken in diverse environments and poses are used to simulate images stored in the IT devices. A CNN is trained on the NIST and Flickr images for this study. The experimental results demonstrate that the CNN outperforms the MorphoTrak's algorithm by 2.5%, achieving accuracy of 98.8% on the NIST database. When the CNN is trained on the NIST database to detect Flickr images, the accuracy drops to 65.8%. It implies that the NIST database is not an ideal database for training algorithms to detect tattoo images in IT devices of suspects. However, when the training database size increases, the detection performance improves.

In the field of environment and health studies, recent trends have focused on the identification of contaminants of emerging concern (CEC). This is a complex, challenging task, as resources, such as compound databases (DBs) and mass spectral libraries (MSLs) concerning these compounds are very poor. This is particularly true for semi polar organic contaminants that have to be derivatized prior to gas chromatography-mass spectrometry (GC-MS) analysis with electron impact ionization (EI), for which it is barely possible to find any records. In particular, there is a severe lack of datasets of GC-EI-MS spectra generated and made publicly available for the purpose of development, validation and performance evaluation of cheminformatics-assisted compound structure identification (CSI) approaches, including novel cutting-edge machine learning (ML)-based approaches [1].We set out to fill this gap and support the machine learning-assisted compound identification, thus aiding cheminformatics-assisted identification of silylated derivatives in GC-MS laboratories working in the field of environment and health. To this end, we have generated 12 datasets of GC-EI-MS spectra, six of which contain GC-EI-MS spectra of trimethylsilyl (TMS) and six GC-EI-MS spectra of tert-butyldimethylsilyl (TBDMS) derivatives. Four of these datasets, named testing datasets, contain mass spectra acquired by the authors. They are available in full, together with corresponding metadata. Eight datasets, named training datasets, were derived from mass spectra in the NIST 17 Mass Spectral Library. For these, we have only made the metadata publicly available, due to licensing reasons.For each type of derivative, two testing datasets are generated by acquiring and processing GC-EI-MS spectra, such that they include raw and processed GC-EI-MS spectra of TMS and TBDMS derivatives of CECs, along with their corresponding metadata. The metadata contains IUPAC name, exact mass, molecular formula, InChI, InChIKey, SMILES and PubChemID, of each CEC and CEC-TMS or CEC-TBDMS derivative, where available. Eight GC-EI-MS training datasets are generated by using the National Institute of Standards and Technology (NIST)/U.S. Environmental Protection Agency (EPA)/National Institute of Health (NIH) 17 Mass Spectral Library. For each derivative type (TMS and TBDMS), four datasets are given, each corresponding to an original dataset obtained from NIST/EPA/NIH 17 and three variants thereof, obtained after each of the filtering steps of the procedure described below. Only the metadata about the training datasets are available, describing the corresponding NIST/EPA/NIH 17 entires: These include the compound name, CAS Registry number, InChIKey, exact mass, Mw, NIST number and ID number.The datasets we present here were used to train and test predictive models for identification of silylated derivatives built with ML approaches [4]. The models were built by using data curated from the NIST Mass Spectral Library 17 [2] and the machine learning approach of CSI:Output Kernel Regression (CSI:OKR) [2]. Data from the NIST Mass Spectral Library 17 are commercially available from the National Institute of Standards and Technology (NIST)/U.S. Environmental Protection Agency (EPA)/National Institute of Health (NIH) and thus cannot be made publicly available. This highlights the need for publicly available GC-EI-MS spectra, which we address by releasing in full the four testing datasets.

In recent years, research efforts and measurement capabilities in biological science have significantly increased at the National Institute of Standards and Technology (NIST). Biological experiments are often performed by NIST physicists, chemists, and engineers who are not traditionally trained in biological safety protocols. A biosafety working group comprised of research scientists from across NIST was formed to address the need for an expanded, formalized biosafety program to ensure proper training and protocols for all biological experiments performed within the organization. With the support of NIST management, a dedicated Biosafety Officer was hired to formalize the biological safety program, and new requirements were established for training of staff and visiting scientists, registration of biohazardous materials, inspection of biological laboratories, and audits of the program to ensure continued compliance with internal biosafety requirements and other relevant biosafety regulations and guidelines.

Standards provide critical benefits across a wide variety of contexts, including safety and health, environmental protection, and quality of products and services. However, while these benefits are generally acknowledged, estimating the social and economic value of standards and determining how specific entities and activities influence their development require careful analysis. In October of 2018, the National Institute of Standards and Technology (NIST) asked the RAND Corporation to estimate the benefit of NIST’s research contributing to particular fire safety standards. The original objectives of the project were to (1) document the role of the NIST in the standards development process, (2) estimate the value these standards provide to society, and (3) thereby inform the economic value of NIST’s contribution to these standards. This report presents results for the first two objectives. Given that NIST’s contribution is one of several inputs combining to create these standards, NIST’s share of the credit for their value could not be quantified. Our analysis focused on case studies in standards for home smoke alarms and for protecting structures at the wildland-urban interface (WUI). Our analysis draws on a wide variety of qualitative and quantitative methods to holistically describe the impacts of these standards and NIST’s role in their development. The intended audience of this report includes those who work on fire safety research, fire safety standards, building codes, and technology transfer. The conclusions presented here may also be of interest for broader resource allocation and federal budget justification purposes. Finally, this report was written to be accessible to any interested members of the general public.