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At least 1,567 records · Page 87

Cybersecurity and Privacy Aspects of Smart Contracts in the Energy Domain

Smart contracts (SCs) are a set of logical procedures that can run by individual peers participating within a Distributed Ledger Technology (DLT) network. By design, smart contracts inherit many of the benefits of DLT, including its immutability, scalability, and security properties. Nevertheless, they may introduce additional attack vectors, which can lead to cybersecurity explorations that could jeopardize the end-application ability to operate as intended or result in data leaks, and privacy violations. In this work, an exploration of known problems, and possible attack scenarios will be presented. This is followed by a set of proposed best practices and mitigation strategies that are intended to assist developers, researchers, and other relevant stakeholders to develop secure SC implementations.

Sebastian Cardenas, David J.↗

MCNP6. Simulating Correlated Data in Fission Events

This report is a series of slides discussing the MCNP6 code and its status in simulating fission. Applications of interest include global security and nuclear nonproliferation, detection of special nuclear material (SNM), passive and active interrogation techniques, and coincident neutron and photon leakage.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data

Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.

Brown, Molly E.↗

Botnet behaviour analysis: How would a data analytics-based system with minimum a priori information perform?

Botnets, as one of the most aggressive threats, has used different techniques, topologies, and communication protocols in different stages of their lifecycle since 2003. Hence, identifying botnets has become very challenging specifically given that they can upgrade their methodology at any time. Various detection approaches have been proposed by the cyber-security researchers, focusing on different aspects of these threats. In this work, 5 different botnet detection approaches are investigated. These systems are selected based on the technique used and type of data used where 2 are public rule–based systems (BotHunter and Snort) and the other 3 use machine learning algorithm with different feature extraction methods (packet payload based and traffic flow based). On the other hand, 4 of these systems are based on a priori knowledge while one is using minimum a priori information. The objective here is to evaluate the effectiveness of these approaches under different scenarios (eg, multi-botnet and single-botnet classifications) as well as exploring how a system with minimum a priori information would perform. The goal is to investigate if a system with minimum a priori information could result in a competitive performance compared to systems using a priori knowledge. The evaluation is shown on 24 publicly available botnet data sets. Results indicate that a machine learning–based system with minimum a priori information not only achieves a very high performance but also generalizes much better than the other systems evaluated on a wide range of botnet structures (from centralized to decentralized botnets).

97 MATHEMATICS AND COMPUTING↗

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement. Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.

97 MATHEMATICS AND COMPUTING↗

Akatosh: Automated Cyber Incident Verification and Impact Analysis

Akatosh, a U.S. Department of Homeland Security Transition to Practice Program (TTP) project developed by Oak Ridge National Laboratory with industry and academic partnership, enables automated, real-time forensic analysis of endpoints after malware-attacks and other cyber security incidents by automatically maintaining detailed snapshots of host-level activity on endpoints over time. It achieves this by integrating intrusion detection systems (IDS) with forensic tools. The combination allows Akatosh to collect vast amounts of endpoint data and assists in verifying, tracking, and analyzing endpoints in real time. This provides operations personnel and analysts as well as managers and executives with continuous feedback on the impact of malicious software and other security incidents on endpoints in their network.

Smith, Jared M.↗

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project KDP-C Review

The topics discussed are the UAS-NAS project life-cycle and ARMD thrust flow down, as well as the UAS environments and how we operate in those environments. NASA's Armstrong Flight Research Center at Edwards, CA, is leading a project designed to help integrate unmanned air vehicles into the world around us. The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS in the NAS, will contribute capabilities designed to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The project falls under the Integrated Systems Research Program office managed at NASA Headquarters by the agency's Aeronautics Research Mission Directorate. NASA's four aeronautics research centers - Armstrong, Ames Research Center, Langley Research Center, and Glenn Research Center - are part of the technology development project. With the use and diversity of unmanned aircraft growing rapidly, new uses for these vehicles are constantly being considered. Unmanned aircraft promise new ways of increasing efficiency, reducing costs, enhancing safety and saving lives 460265main_ED10-0132-16_full.jpg Unmanned aircraft systems such as NASA's Global Hawks (above) and Predator B named Ikhana (below), along with numerous other unmanned aircraft systems large and small, are the prime focus of the UAS in the NAS effort to integrate them into the national airspace. Credits: NASA Photos 710580main_ED07-0243-37_full.jpg The UAS in the NAS project envisions performance-based routine access to all segments of the national airspace for all unmanned aircraft system classes, once all safety-related and technical barriers are overcome. The project will provide critical data to such key stakeholders and customers as the Federal Aviation Administration and RTCA Special Committee 203 (formerly the Radio Technical Commission for Aeronautics) by conducting integrated, relevant system-level tests to adequately address safety and operational challenges of national airspace access by unmanned aircraft systems, or UAS. In the process, the project will work with other key stakeholders to define necessary deliverables and products to help enable such access. Within the project, NASA is focusing on five sub-projects. These five focus areas include assurance of safe separation of unmanned aircraft from manned aircraft when flying in the national airspace; safety-critical command and control systems and radio frequencies to enable safe operation of UAS; human factors issues for ground control stations; airworthiness certification standards for UAS avionics and integrated tests and evaluation designed to determine the viability of emerging UAS technology. Five Focus Areas of the UAS Integration in the NAS Project Separation Assurance Provide an assessment of how planned Next Generation Air Transportation System (NextGen) separation assurance systems, with different functional allocations, perform for UAS in mixed operations with manned aircraft Assess the applicability to UAS and the performance of NASA NextGen separation assurance systems in flight tests with realistic latencies and uncertain trajectories Assess functional allocations ranging from today's ground-based, controller-provided aircraft separation to fully autonomous airborne self-separation Communications Develop data and rationale to obtain appropriate frequency spectrum allocations to enable safe and efficient operation of UAS in the NAS Develop and validate candidate secure safety-critical command and control system/subsystem test equipment for UAS that complies with UAS international/national frequency regulations, standards and recommended practices and minimum operational and aviation system performance standards for UAS Perform analysis to support recommendations for integration of safety-critical command and control systems and air traffic control communications to ensure safe and efficient operation of UAS in the NAS Human Systems Integration Develop a research test bed and database to provide data and proof of concept for GCS - ground control station - operations in the NAS Coordinate with standards organizations to develop human-factors guidelines for GCS operation in the NAS Certification Define a UAS classification scheme and approach to determining Federal Aviation Regulation airworthiness requirements applicable to all UAS digital avionics Provide hazard and risk-related data to support development of type design criteria and best development practices Integrated Tests and Evaluation Integrate and test mature concepts from technical elements to demonstrate and test viability Evaluate the performance of technology development in a relevant environment (full-mission, human-in-the-loop simulations and flight tests)

outreach↗

Cybersecurity Considerations and Research Pathways for Grid-Interactive Efficient Buildings

Federal facilities serve critical missions and functions that require safe, reliable, and efficient operations. Digitization of several facility operations has increased the cost-effectiveness of energy usage and optimization of energy system performance. As the building controls landscape shifts to become more connected and smarter, building operators now face unique opportunities and challenges to adopt smart enabled devices that can lower energy usage while also optimizing building system performance. The grid-interactive efficient buildings (GEB) initiative aims to make buildings cleaner and more flexible through these smart devices. Smart enabled devices allow greater connectivity and control through remote operations and provide crucial data for analytics and increased efficiency. GEBs enable demand flexibility that has the potential to reduce electrical costs and transform the grid edge where buildings connect to power grids. This operation of interconnected systems, if not designed with cybersecurity practices, causes security gaps and introduces potential attack paths by adversarial and non-adversarial entities leading to disruption of operations.

building controls↗

Rolling Process Modeling Report. Finite-Element Model Validation and Parametric Study on various Rolling Process parameters

Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum alloy plate-type fuel for high-performance research reactors in the United States. This work supports the U.S. Department of Energy National Nuclear Security Administration’s Office of Material Management and Minimization Reactor Conversion Program. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll-separating forces for various rolling mill geometries for PNNL, Babcock & Wilcox Co., Y-12 National Security Complex, Los Alamos National Laboratory, and Idaho National Laboratory. The model developed and presented in a previous report has been subjected to further validation study using new sets of experimental data generated from a rolling mill at PNNL. Simulation results of both hot rolling and cold rolling of uranium-10% molybdenum coupons have been compared with experimental results. The model was used to predict roll-separating forces at different temperatures and reductions for five rolling mills within the National Nuclear Security Administration Fuel Fabrication Capability project. This report also presents initial results of a finite-element model microstructure-based approach to study the surface roughness at the interface between zirconium and uranium-10% molybdenum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Empowering Critical Infrastructure Communication with Secure 5G Private Networks

With the transformational New Radio- Unlicensed (NR-U), 5G network can be operated with unlicensed and shared spectrum. Private 5G networks without any licensed bands, which are both highly expensive and usually available to only large commercial wireless providers, can now be used for a whole range of new applications including smart factories, warehouses, connected cars and drones. 5G’s support of a) massive machine type communication (mMTC) for a large number of connected devices with b) ultra-reliable low latency communication (URLLC) capability when needed, and c) up to 20 times higher data rate with enhanced mobile broadband (eMBB) than previously available, enables new and powerful capabilities in a wireless network. While these capabilities are transformational, necessary security and reliability requirements have to be satisfied when used in critical infrastructure such as factories, power plants, water systems, ports, and other industrial facilities. 5G standards have introduced significant security improvement over 4G/LTE as well as mitigations for new attack surfaces created by changes in the 5G network. This talk will discuss these security improvements and whether they meet the security properties required for mission critical communication over wireless.

5G↗

Evaluating ESA CCI Soil Moisture in East Africa

To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASAs Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R greater than 0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

Amy McNally↗

Data Mining Techniques to Estimate Plutonium, Initial Enrichment, Burnup, and Cooling Time in Spent Fuel Assemblies

The Next Generation Safeguards Initiative (NGSI), Office of Nonproliferation and Arms Control (NPAC), National Nuclear Security Administration (NNSA) of the U.S. Department of Energy (DOE) has sponsored a multi-laboratory, university, international partner collaboration to (1) detect replaced or missing pins from spent fuel assemblies (SFA) to confirm item integrity and deter diversion, (2) determine plutonium mass and related plutonium and uranium fissile mass parameters in SFAs, and (3) verify initial enrichment (IE), burnup (BU), and cooling time (CT) of facility declaration for SFAs. A wide variety of nondestructive assay (NDA) techniques were researched to achieve these goals [Veal, 2010 and Humphrey, 2012]. In addition, the project includes two related activities with facility-specific benefits: (1) determination of heat content and (2) determination of reactivity (multiplication). In this research, a subset of 11 integrated NDA techniques was researched using data mining solutions at Los Alamos National Laboratory (LANL) for their ability to achieve the above goals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Data Mining Techniques to Estimate Plutonium, Initial Enrichment, Burnup, and Cooling Time in Spent Fuel Assemblies

The Next Generation Safeguards Initiative (NGSI), Office of Nonproliferation and Arms Control (NPAC), National Nuclear Security Administration (NNSA) of the U.S. Department of Energy (DOE) has sponsored a multi-laboratory, university, international partner collaboration to (1) detect replaced or missing pins from spent fuel assemblies (SFA) to confirm item integrity and deter diversion, (2) determine plutonium mass and related plutonium and uranium fissile mass parameters in SFAs, and (3) verify initial enrichment (IE), burnup (BU), and cooling time (CT) of facility declaration for SFAs. A wide variety of nondestructive assay (NDA) techniques were researched to achieve these goals [Veal, 2010 and Humphrey, 2012]. In addition, the project includes two related activities with facility-specific benefits: (1) determination of heat content and (2) determination of reactivity (multiplication). In this research, a subset of 11 integrated NDA techniques was researched using data mining solutions at Los Alamos National Laboratory (LANL) for their ability to achieve the above goals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DICOMs, Missiles, and Metadata: The U.S. Nuclear Weapons Program Leverages a Medical Standard

Digital Imagine and Communications in Medicine (DICOM) images, although most commonly used in medical settings, have been widely adopted by the United States Department of Energy (DOE) for capturing images of the internal components in a nuclear weapon. DICOMs, a lesser-known file format that combine nested metadata structures with complex image data-including multiple planes, frames, and high resolution-require the creation of access copies to support usability within the DOE. Used primarily for ensuring the safety, security, and reliability of the U.S. nuclear stockpile, the Los Alamos National Laboratory (LANL)’s DICOM images and corresponding image metadata must be accessible to scientists and researchers via our institutional centralized databases. This paper describes the author's creation of a Python script that converts DICOM images into accessible, archive-friendly TIFF files while preserving key image data and metadata.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

IER-517: Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK)

Nuclear criticality experiments are essential to the validation of nuclear data used in simulation software. The quality of nuclear data becomes paramount as simulation software becomes more relied upon for criticality safety studies and designs of nuclear systems. To improve the quality of nuclear data, experimenters can design critical experiments that are sensitive to isotope reaction pairs in materials of interest. The efforts conducted by the Organisation for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA) Working Party on Nuclear Criticality Safety (WPNCS) Subgroup 8: Preservation of Expert Knowledge and Judgement Applied to Criticality Benchmarks (SG8) to categorize benchmarks according to their usefulness for nuclear data validation have been of great importance. Based on the OECD studies benchmark experiments included in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook are concisely used by nuclear data evaluators, criticality safety engineers and others to validate nuclear data and simulation results. A lack of benchmarks sensitive to molybdenum in the (ICSBEP), particularly in the intermediate range, was noted by Los Alamos National Laboratory (LANL), the French Institut de Radioprotection et de Sûreté Nucléaire (IRSN), and Y-12 National Security Site prompting them to submit a joint integral experiment request to the Nuclear Criticality Safety Program (NCSP) in 2019. The request included both HEU and Plutonium systems in order to validate differential nuclear data focusing on the intermediate energy range but also includes thermal and fast configurations. This document represents the preliminary design work for a series of molybdenum integral experiments known as Molybdenum Optimized Benchmark System Demonstrating Integral Correlations (MOBY DICK).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Redefining the U.S. Agenda for Nuclear Disarmament, Analysis and Reflections

With Lewis Dunn’s paper on nuclear disarmament diplomacy, we are inaugurating a new monograph series under the auspices of the Center for Global Security Research at Lawrence Livermore National Laboratory. The series will explore complex emerging challenges in the emerging security environment as they bear on issues of deterrence, assurance, and strategic stability. Our goal is to explore these issues deeply enough to provide significant new understanding that is technically informed and policy relevant. Our premise is that thoughtful students of international security affairs continue to value such in-depth analysis as a way to help make sense of the large flow of data and opinion that reaches all of us on a daily basis. Our ambition is to generate four to six such papers per year on especially salient topics. The views expressed in these papers are those of the author and should not be attributed to the Center, the Laboratory, or the U.S. government. This inaugural paper addresses one of the key questions facing national leadership seven to eight years after President Obama’s April 2009 remarks in Prague and his commitment to take practical steps towards the long-term goal of the elimination of nuclear weapons. In the interim, some important steps have been taken. But there have also been many disappointments. The new presidential administration will face a security landscape quite different from that of eight years ago and must reassess U.S. priorities and approaches. As Lewis Dunn argues, some will be tempted to walk away entirely from the disarmament agenda, while others will advocate even more forcefully for unilateral U.S. steps to further reduce the role and number of nuclear weapons in its posture. Dr. Dunn sets out his own vision of how to adapt and carry forward the disarmament agenda, in a manner informed by developments in the security environment that point to a continuing role for nuclear deterrence. The result is both fresh and compelling.

99 GENERAL AND MISCELLANEOUS↗

Cross-Layered Cyber-Physical Power System State Estimation towards a Secure Grid Operation

In the Smart Grid paradigm, this critical infrastructure operation is increasingly exposed to cyber-threats due to the increased dependency on communication networks. An adversary can launch an attack on a power grid operation through False Data Injection into system measurements and/or through attacks on the communication network, such as flooding the communication channels with unnecessary data or intercepting messages. A cross-layered strategy that combines power grid data, communication grid monitoring and Machine Learning based processing is a promising solution for detecting cyberthreats. In this paper, an implementation of an integrated solution of a cross-layer framework is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection of anomalies in the operation of power grid. IEEE 118-bus system is built in Simulink to provide a power grid testing environment and communication network data is emulated using SimComponents. The performance of the framework is investigated under various FDI and communication attacks.

cyber security, network security, cyber-physical s↗

ANALYZING THE LARGEST SPECTROSCOPIC DATA SET OF STRIPPED SUPERNOVAE TO IMPROVE THEIR IDENTIFICATIONS AND CONSTRAIN THEIR PROGENITORS

Using the largest spectroscopic data set of stripped-envelope core-collapse supernovae (stripped SNe), we present a systematic investigation of spectral properties of Type IIb SNe (SNe IIb), Type Ib SNe (SNe Ib), and Type Ic SNe (SNe Ic). Prior studies have been based on individual objects or small samples. Here, we analyze 242 spectra of 14 SNe IIb, 262 spectra of 21 SNe Ib, and 207 spectra of 17 SNe Ic based on the stripped SN data set of Modjaz et al. and other published spectra of individual SNe. Each SN in our sample has a secure spectroscopic ID, a date of V -band maximum light, and most have multiple spectra at different phases. We analyze these spectra as a function of subtype and phase in order to improve the SN identification scheme and constrain the progenitors of different kinds of stripped SNe. By comparing spectra of SNe IIb with those of SNe Ib, we find that the strength of H α can be used to quantitatively differentiate between these two subtypes at all epochs. Moreover, we find a continuum in observational properties between SNe IIb and Ib. We address the question of hidden He in SNe Ic by comparing our observations with predictions from various models that either include hidden He or in which He has been burnt. Our results favor the He-free progenitor models for SNe Ic. Finally, we construct continuum-divided average spectra as a function of subtype and phase to quantify the spectral diversity of the different types of stripped SNe.

79 ASTRONOMY AND ASTROPHYSICS↗