ITL Newsletter for January - February 2019




information technology laboratory



Face Recognition


Between 2014 and 2018, facial recognition software got 20 times better at searching a database to find a matching photograph, according to the National Institute of Standards and Technology’s (NIST) evaluation of 127 software algorithms from 39 different developers—the bulk of the industry. The findings, together with other data in a NIST report published today, point to a rapidly advancing marketplace for face-based biometric matching algorithms.

The new publication, NIST Interagency Report (NISTIR) 8238, Ongoing Facial Recognition Vendor Test (FRVT), updates the agency’s previous evaluations of facial recognition software, 2010’s NISTIR 7709 and 2014’s NISTIR 8009. Comparing the reports indicates that the field of developers has grown and that, broadly speaking, facial recognition software is improving at an increasing rate.

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Companies in every industry need software that their employees and customers can easily learn to use without error, but for years there was no way for them to evaluate the usability of software before or after purchase. NIST usability experts brought together hundreds of organizations to develop an international reporting standard to improve software usability.



Wireless Infusion Pump Security

Infusion pumps were once standalone instruments that interacted only with the patient or medical provider. With technological improvements designed to enhance patient care, new wireless versions of the pumps are connected to a variety of systems, networks and other devices—which can introduce cybersecurity risks. Through collaboration with industry, NIST’s National Cybersecurity Center of Excellence (NCCoE) demonstrated one approach that health care providers can use to enhance security and improve the safety and delivery of health care to patients.



On November 1, 2018, ITL Information Access Division organized the very successful 7th annual Science Day mini-conference at NIST. Science Day is a celebration of the work of NIST-ITL scientist and an opportunity for them to present posters and demos of their work to their peers and others at NIST, as well as hearing from distinguished speakers on relevant subjects of interest. This year’s Science Day was held in the NIST library, and focused on Artificial Intelligence. Highlights from Science Day 2018 include: 61 poster presentations, 16 demonstrations, and 6 talks from distinguished speakers both inside and outside of NIST. Distinguished speakers included Drs JamesKurose/NSF, Abdou Yousef/NIST, Ian Soboroff/NIST, John Prager/IBM, Yang Gao/NIST and David Brin/Author & Scientist. This year’s event also yielded a unique collaboration with NIST's Engineering Laboratory where one of their scientist provided a demonstration robot and support for the venue. 

Science Day Poster


Shahram Orandi

Shahram Orandi, Chief

In a world where technologies such as fingerprint scanners and facial recognition devices evolve on a seemingly regular basis, the Information Access Division (IAD) provides standards and measurements to accelerate this evolution. IAD not only helps complex technologies grow but also tests them to ensure they are used correctly and efficiently.

IAD supports technologies used to access potentially complex information from multimedia devices or biometric devices, such as digital video recording systems or iris scanners. Through collaborations with industry, academia, and the federal government, IAD enables the advancement of these technologies for commercial usage.







Adam Pintar, Statistical Engineering Division, Received a Group Gold Medal Award

For technical innovations to develop new maps of U.S. extreme wind speeds, used for the design of structures. The underpinning analysis was the first to realistically account for risk consistency, multiple storm types, and regional variation of wind climate. The team also worked to ensure that the new maps were incorporated in the American Society of Civil Engineers' national standard for the design of buildings and other structures for wind loads. This greatly improved the science basis of the standard, enabling safe and more economical designs for buildings and infrastructure. 

Dennis Leber and James Filliben, Statistical Engineering Division, Received a Group Bronze Medal Award

For exceptional leadership in founding the ASTM Committee F45 on driverless automatic guided industrial vehicles, and for providing the technical basis of the committee’s first four performance standards for automatic/automated/autonomous unmanned ground vehicles (A-UGVs). A-UGVs are used to automate delivery of parts, tools, supplies, and other materials in applications such as manufacturing, warehousing, and medical delivery. A-UGV capabilities have been evolving rapidly, but there were no standard methods for describing or assessing A-UGV performance and capabilities. The team's outstanding efforts have enabled significant progress in addressing these gaps in just two years.

Peter Mell, Computer Security Division, Received a Bronze Medal Award

For technical advances in computer-network defense methods used in government and industrial systems. His insight and creativity led to vastly improved algorithms used in the field of intrusion detection and access control. Specifically, he (a) developed an improved network scan-detection algorithm that the U.S. Army Research Laboratory has deployed in an operational network; (b) conducted a novel analysis of network anomaly-detection leading to a new understanding of intrusion detection; and (c) developed improved algorithms for scalable access control. This work has provided both practical (fielded) advances in network intrusion detection, and advances in the science of network defense.

Blaza Toman, Statistical Engineering Division, Received a Group Bronze Medal Award

For the development of rigorous analytical methods and data-evaluation processes for the determination of chemical purity, and for transfer of this technology to the private sector for the development of a new class of primary Standard Reference Materials. Knowledge of chemical purity is essential for accurate amount-of-substance measurements and for establishing the metrological traceability of these results to the International System of Units (SI). The team’s processes are applicable to a range of NIST’s measurement services, with applications that extend from healthcare delivery to forensic purity assessment of seized drugs. 

Ya-Shian Li-Baboud, Software and Systems Divisions, Received a Group 2018 Edward Bennett Rosa Award

For outstanding leadership and technical excellence in initiating and developing performance test methods that have been adopted as international standards for 3D imaging systems used in a wide range of critical applications. The team identified the need for measurements and standards for a burgeoning new sensing technology, convened the stakeholders, and formed a new ASTM standards committee. The team's rigorous experiments, analyses, and crafting of test methods and artifacts provided the technical foundations for the first-ever standards that measure key performance aspects of 3D imaging systems, guiding system improvements and enabling users to compare different systems and reduce adoption risks.

Patricia Toth, Computer Security Division, Received a 2018 George A. Uriano Award

For outstanding contributions to the MEP National Network to assist U.S. manufacturers in implementing critical cybersecurity protections. In November 2017, she published NIST Handbook 162, the “NIST MEP Cybersecurity Self-Assessment Handbook” to help U.S. manufacturers assess their implementation of NIST SP 800-171 security requirements in response to Defense Federal Acquisition Regulation Supplement (DFARS) cybersecurity requirements. Between November 2017 and April 2018, NIST Handbook 162 was downloaded from the NIST webpages nearly 15,000 times, and Toth has trained manufacturing specialists in its usage in most of the 51 MEP Centers around the nation. Her leadership is creating a vital cybersecurity assistance practice for MEP Centers nationwide.

Michael Donahue and Donald Porter, Applied and Computational Mathematics Division, Received the 2018 Jacob Rabinow Applied Research Award

For their initiative to improve the state of the art in nanomagnetic modeling, the computational simulation of magnetic phenomena at the nanoscale, within the research community. They have very carefully engineered a software tool that is usable, flexible, adaptable, and extensible. It is now the most widely used nanomagnetics modeling system in the world. More than 2,500 journal articles (11 in Science and Nature) and 18 U.S. patent applications reference use of their system, attesting to the magnitude of its impact on U.S. innovation.


Automation Support for Security Control Assessments (NISTIR 8011)

The NISTIR 8011 volumes each focus on an individual information security capability, adding tangible detail to the more general overview given in NISTIR 8011 Volume 1, and providing a template for transition to a detailed, NIST guidance -based automated assessment. This document, Volume 3 of NISTIR 8011, addresses the Software Asset Management (SWAM) information security capability. The focus of the SWAM capability is to manage risk created by unmanaged or unauthorized software on a network. Unmanaged or unauthorized software is a target that attackers can use as a platform from which to attack components on the network.

Ongoing Face Recognition Vendor Test (FRVT) Part 2: Identification (NISTIR 8238)

This report documents performance of face recognition algorithms applied to the one-to-many identification of faces appearing in portrait images. The primary dataset is comprised of 26.6 million reasonably well controlled live photos of 12.3 million individuals. Three smaller datasets containing more unconstrained photos are used also. The report will be useful for the comparison of algorithms, and for assessing absolute capability of face recognition with portrait images.

SATE V Report: Ten Years of Static Analysis Tool Expositions (NIST Special Publication 500-326)

Software assurance has been the focus of the National Institute of Standards and Technology (NIST) Software Assurance Metrics and Tool Evaluation(SAMATE) team for many years. The Static Analysis Tool Exposition (SATE) is one of the team’s prominent projects to advance research in and adoption of static analysis, one ofseveral software assurance methods. This report describes our approach and methodology. It then presents and discusses the results collected from the fifth edition of SATE.

Tattoo Recognition Technology - Evaluation (Tatt-E) Performance of Tattoo Identification Algorithms (NISTIR 8232)

NIST performed a large-scale empirical evaluation of tattoo recognition algorithms. The test leveraged large operational datasets comprised of tattoo images from law enforcement databases, enabling evaluation with enrollment database sizes of up to 100,000. NIST employed a lights-out, black-box testing methodology designed to model operational reality where software is shipped and used as-is, without algorithmic training. Core tattoo identification accuracy was baselined over tattoo images used as-is, then traded off against gallery size and search speed. The effects of cropping around the primary tattoo content, skintone, contrast, and tattoo-to-image ratio were assessed, and matching accuracy on sketch images and tattoos collected in the short-wave infrared (SWIR) spectrum are also reported. In addition, performance on algorithmic capability to do tattoo detection and tattoo localization as separate tasks are also documented.






Federal Computer Security Managers' Forum




NIST Threshold Crytography Workshop 2019


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