Results for “access pattern” — Page 17

DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Single-Event Effects in the Peripheral Circuitry of a Commercial Ferroelectric Random Access Memory

This paper identifies the failure modes of a commercial 130-nm ferroelectric random access memory. The devices were irradiated with heavy-ion and pulsed focused X-ray beams. Various failure modes are observed, which generate characteristic error patterns, affecting isolated bits, words, groups of pages, and sometimes entire regions of the memory array. Furthermore, the underlying mechanisms are discussed.

42 ENGINEERING↗

DOE OSTI2022

Investigation of the effects of passive pre-chamber nozzle pattern and ignition system on engine performance and emissions

The impact of passive pre-chamber (PC) internal volume, nozzle hole pattern (i.e. with and without a central axial nozzle), and PC igniter plug type on performance and emissions was investigated in an optically accessible, single-cylinder, gasoline research engine. The two PC igniter plugs investigated were a conventional inductive coil spark plug and a nanosecond repetitively pulsed (NRP) plasma discharge system previously demonstrated to accelerate early flame propagation. The baseline PC design featured a funnel shaped internal volume with a PC tip that contained six radial nozzles and a larger central axial nozzle. Two additional PC tip geometries were evaluated where either the baseline internal volume was increased or the axial nozzle was removed and the radial nozzle diameters were increased. A sweep of charge equivalence ratios ( ϕ) from nearly stoichiometric to the lean limit was performed for a fixed engine speed (1300 revolutions per minute), and engine load (3.5 bar gross indicated mean effective pressure). Time-resolved PC and main chamber (MC) pressure data as well as MC emissions data were collected to analyze engine performance and emissions characteristics. Combustion in the MC was further investigated using high-speed excited methylidyne radical (CH*) chemiluminescence imaging. Collected results highlighted that while all PC tips and ignition systems exhibited similar performance and emissions down to ϕ = 0.8, relevant differences in thermal efficiency and emissions for leaner charge mixtures were observed, with the results highly dependent on the nozzle pattern and ignition system. Major deviations were correlated to preferential de-pressurization of the PC through the axial nozzle for lean conditions that was not observed for mixture conditions closer to stoichiometric. Results show that a combination of radial and axial nozzle patterns in the PC extended lean-stability limits at the low-load condition evaluated. Further benefits were observed with the use of NRP ignition systems due to faster combustion within the PC volume provided that the volume was sufficiently large.

Di Sabatino, Francesco↗

DOE OSTI2017

Travel patterns and characteristics of low-income subpopulation in New York state

Studies have shown that people residing in poverty face more mobility challenges in their daily travels as compared to those living in higher income households. In many cities, the lack of a public transportation systems and investments in low-income areas are making it difficult for those living in poverty to access jobs, goods, and services (schools, groceries, health cares, etc. In this study, Oak Ridge National Laboratory was tasked by the New York State (NYS) Department of Transportation to conduct a detailed examination of the travel behaviors and identify patterns and trends of the low-income residents within NYS. The 2009 National Household Travel Survey data was used as the primary information source to analyze subjects associated with poverty and mobility, as well as to address questions such as are there differences in traveler demographics between the low-income population and those of others who live in various NYS regions (e.g., New York City, other urban areas of NYS)? How do they compare with the population at large (e.g., rest of the country) or with findings from previous years (i.e., trend)? Are there any regional differences (e.g., urban versus rural)? Do any unique travel characteristics or patterns exist within the low-income group? Through this study, various key findings on low-income population sizes, household characteristics, travel patterns, and mobility limitations were identified and summarized in this report.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Population Count on Intel® CPU, GPU, and FPGA

Population count is a primitive used in many applications. Commodity processors have dedicated instructions for achieving high-performance population count. Motivated by the productivity of high-level synthesis and the importance of population count, in this paper we investigated the OpenCL implementations of population count algorithms, and evaluated their performance and resource utilizations on an FPGA. Based on the results, we select the most efficient implementation. Then we derived a reduction pattern from a representative application of population count. We parallelized the reduction with atomic functions, and optimized it with vectorized memory accesses, tree reduction, and compute-unit duplication. We evaluated the performance of the reduction kernel on an Intel (R) Xeon (R) CPU and an Intel (R) IrisT Pro integrated GPU, and an FPGA card that features an Intel (R) Arria (R) 10 FPGA. When DRAM memory bandwidth is comparable on the three computing platforms, the FPGA can achieve the highest kernel performance for large workload. On the other hand, we described performance bottlenecks on the FPGA. To make FPGAs more competitive in raw performance compared to high-performant CPU and GPU platforms, it is important to increase external memory bandwidth, minimize data movement between a host and a device, and reduce OpenCL runtime overhead on an FPGA.

heterogeneous computing↗

DOE OSTI2024

MetaPoL: Immersive VR based Indoor Patterns of Life (PoL) and Anomalies Data Generation for Insider Threat Modeling in Nuclear Security

Insider threats are perhaps the most serious challenges that nuclear and radiological security systems face. Insiders pose such a great threat due to their access, authority, and knowledge, granting them opportunities to bypass dedicated nuclear and radiological security elements. For example, in one of the latest major insider threat incidents to nuclear security, the Doel-4 nuclear powerplant in Belgium suffered a shutdown, the threat of nuclear materials diversion, and long-term loss of tens of millions of dollars. Seven years of investigation concluded that it was an inside job and attempted sabotage. In this regard, there is an immediate need for R&D and technology integration in the domain of modeling indoor Patterns-of-Life (PoL) and anomaly detection. This can be achieved by using datasets of facility users’ mobility and activity, which can support the design of algorithms for insider threat modeling and detection. However, due to classification, privacy, sensitivity, and safety protocols, such datasets from real physical nuclear reactor facilities are not only hard to share, but also not always feasible to deploy and collect. Aiming to find an alternate solution, our proposed demonstration work - MetaPoL, is the first-ever (for the application space) immersive VR (virtual reality) environment of a real-world secure facility and allows users to move-and-stay through the designed indoor physical layout and also encounter NPCs (non-player characters) that emulate other facility users. In the MetaPoL an interactive user performs realistic spatio-temporal movement, dwelling and activities using a Meta Quest Pro VR headset, and that generates high-frequency (in time) high-resolution (in space) indoor spatial-temporal datasets that are valuable for PoL modeling and anomaly detection research specifically for insider threat modeling and detection mission. Such generated realistic, rich in context, and mission specific datasets can boost AI/Machine Learning based research for modeling and detecting insider threats in nuclear security and nonproliferation.

Gunaratne, Chathika↗

DOE OSTI2019

Detection of Spatiotemporal Prescription Opioid Hot Spots With Network Scan Statistics: Multistate Analysis

Background: Overuse and misuse of prescription opioids have become significant public health burdens in the United States. About 11.5 million people are estimated to have misused prescription opioids for nonmedical purposes in 2016. This has led to a significant number of drug overdose deaths in the United States. Previous studies have examined spatiotemporal clusters of opioid misuse, but they have been restricted to circular shaped regions. Objective: The goal of this study was to identify spatiotemporal hot spots of opioid users and opioid prescription claims using Medicare data. Methods: We examined spatiotemporal clusters with significantly higher number of beneficiaries and rate of prescriptions for opioids using Medicare payment data from the Centers for Medicare & Medicaid Services. We used network scan statistics to detect significant clusters with arbitrary shapes, the Kulldorff scan statistic to examine the significant clusters for each year (2013, 2014, and 2015) and an expectation-based version to examine the significant clusters relative to past years. Regression analysis was used to characterize the demographics of the counties that are a part of any significant cluster, and data mining techniques were used to discover the specialties of the anomalous providers. Results: We examined anomalous spatial clusters with respect to opioid prescription claims and beneficiary counts and found some common patterns across states: the counties in the most anomalous clusters were fairly stable in 2014 and 2015, but they have shrunk from 2013. In Virginia, a higher percentage of African Americans in a county lower the odds of the county being anomalous in terms of opioid beneficiary counts to about 0.96 in 2015. For opioid prescription claim counts, the odds were 0.92. This pattern was consistent across the 3 states and across the 3 years. A higher number of people in the county with access to Medicaid increased the odds of the county being in the anomalous cluster to 1.16 in both types of counts in Virginia. A higher number of people with access to direct purchase of insurance plans decreased the odds of a county being in an anomalous cluster to 0.85. The expectation-based scan statistic, which captures change over time, revealed different clusters than the Kulldorff statistic. Providers with an unusually high number of opioid beneficiaries and opioid claims include specialties such as physician’s assistant, nurse practitioner, and family practice. Conclusions: Our analysis of the Medicare claims data provides characteristics of the counties and provider specialties that have higher odds of being anomalous. The empirical analysis identifies highly refined spatial hot spots that are likely to encounter prescription opioid misuse and overdose. The methodology is generic and can be applied to monitor providers and their prescription behaviors in regions that are at a high risk of abuse.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Modeling of plasma beta effects on the island divertor transport in the standard configuration of W7-X

The influence of plasma beta effects on the edge plasma transport in the Wendelstein 7-X standard configuration is studied systematically by using EMC3-EIRENE combined with a 3D equilibrium code named HINT. The magnetic topology changes induced by plasma beta effects are significantly reflected in plasma transport behaviors and heat flux patterns on divertor targets. After validating the modeling strategy by comparisons with experimental data, the extended simulations for high performance plasmas show that the threshold separatrix density for accessing the power detachment is reduced in higher beta plasmas. Compared with the vacuum field case, the impurity radiation distributions with finite beta effects are modified in the magnetic island region. The divertor heat flux is distributed more evenly along the toroidal direction on the strike line at the vertical target. The strike line on the horizontal target moves towards the pumping gap with an increase in the plasma beta. In addition, the different pressure profiles with the same central beta also result in a modified heat flux pattern on the divertor targets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Exploring MPI Communication Models for Graph Applications Using Graph Matching as a Case Study

Traditional implementations of parallel graph operations on distributed memory platforms are written using Message Passing Interface (MPI) point to point communication primitives such as Send-Recv (blocking and nonblocking). Apart from this classical model, the MPI community has over the years added other communication models; however, their suitability for handling the irregular traffic workloads typical of graph operations remain comparatively less explored. Our aim in this paper is to study these relatively underutilized communication models of MPI for graph applications. More specifically, we evaluate MPI’s one-sided programming, or Remote Memory Access (RMA), and nearest neighborhood collectives using a process graph topology. There are features in these newer models that are intended to better map to irregular communication patterns, as exemplified in graph algorithms. As a concrete application for our case study, we use distributed memory implementations of a weighted graph matching algorithm to investigate performances of MPI-3 RMA and neighborhood collective operations compared to nonblocking Send- Recv. A matching in a graph is a subset of edges such that no two matched edges are incident on the same vertex. A maximum weight matching is a matching of maximum weight computed as the sum of the weights of matched edges. Algorithms for optimal matching have quadratic complexity and are difficult to parallelize. More importantly, execution of graph matching is dominated by high volume of irregular memory accesses, making it an ideal candidate for studying the effects of various MPI communication models on graph applications at scale. Our neighborhood collectives and RMA implementations yields up to 6× speedup over traditional optimized nonblocking Send-Recv implementations, on thousands of cores of the NERSC Cori supercomputer. We believe the lessons learned from this case study can be adopted to benefit a wider range of graph application codes.

Ghosh, Sayan↗

DOE OSTI2022

A Semiconducting Two‐Dimensional Polymer as an Organic Electrochemical Transistor Active Layer

Abstract Organic electrochemical transistors (OECTs) are devices with broad potential in bioelectronic sensing, circuits, and neuromorphic hardware. Their unique properties arise from the use of organic mixed ionic/electronic conductors (OMIECs) as the active channel. Typical OMIECs are linear polymers, where defined and controlled microstructure/morphology, and reliable characterization of transport and charging can be elusive. Semiconducting two‐dimensional polymers (2DPs) present a new avenue in OMIEC materials development, enabling electronic transport along with precise control of well‐defined channels ideal for ion transport/intercalation. To this end, a recently reported 2DP, TIIP, is synthesized and patterned at 10 µm resolution as the channel of a transistor. The TIIP films demonstrate textured microstructure and show semiconducting properties with accessible oxidation states. Operating in an aqueous electrolyte, the 2DP‐OECT exhibits a device‐scale hole mobility of 0.05 cm 2 V –1 s –1 and a µ C * figure of merit of 1.75 F cm –1 V –1 s –1 . 2DP OMIECs thus offer new synthetic degrees of freedom to control OECT performance and may enable additional opportunities such as ion selectivity or improved stability through reduced morphological modulation during device operation.

2D-polymer↗

DOE OSTI2023

Open and Close-Packed, Shape-Engineered Polygonal Nanoparticle Metamolecules with Tailorable Fano Resonances

In this study, a top-down lithographic patterning and deposition process is reported for producing nanoparticles (NPs) with well-defined sizes, shapes, and compositions that are often not accessible by wet-chemical synthetic methods. These NPs are ligated and harvested from the substrate surface to prepare colloidal NP dispersions. Using a template-assisted assembly technique, fabricated NPs are driven by capillary forces to assemble into size- and shape-engineered templates and organize into open or close-packed multi-NP structures or NP metamolecules. The sizes and shapes of the NPs and of the templates control the NP number, coordination, interparticle gap size, disorder, and location of defects such as voids in the NP metamolecules. The plasmonic resonances of polygonal-shaped Au NPs are exploited to correlate the structure and optical properties of assembled NP metamolecules. Comparing open and close-packed architectures highlights that introduction of a center NP to form close-packed assemblies supports collective interactions, altering magnetic optical modes and multipolar interactions in Fano resonances. Decreasing the distance between NPs strengthens the plasmonic coupling, and the structural symmetries of the NP metamolecules determine the orientation-dependent scattering response.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2021

Organic sulfur fluxes and geomorphic control of sulfur isotope ratios in rivers

Pyrite oxidation plays a critical role in the relationship between weathering and climate, and its impact on the global carbon cycle has previously been constrained through inversion models utilizing observations of river sulfate ($SO^{2–}_{4}$) and its 34 S/ 32 S isotope ratio (δ 34 S SO4 ). However, measurements from some rivers have suggested that SSO4 can be substantially impacted by processes such as microbial sulfate reduction and/or sulfur assimilation and cycling, rather than simply reflecting a weighted mixture of lithologic sulfur sources. To study the prevalence and controls on $SO^{2–}_{4}$ transformations, in this study we measured dissolved major element concentrations and δ 34 S SO4 in river water samples from throughout western Iceland. Our analyses focused on samples from a small catchment hosting the Efri Haukadalsá river, a system with relatively uniform and isotopically constrained basaltic bedrock. We also measured sediment δ 34 S and sulfur speciation using sulfur K-edge X-ray absorption spectroscopy on sediment and vegetation samples from this catchment. Values of dissolved δ 34 S SO4 in the Efri Haukadalsá ranged from 2.5‰ to 23.7‰ and had a linear relationship with Cl – /$SO^{2–}_{4}$ ratios, indicating that $SO^{2–}_{4}$ predominantly derived from basalt weathering and meteoric precipitation. The lower δ 34 S SO4 values were found in fluvial valleys with V-shaped cross sections, while higher values of δ 34 S SO4 occurred in U-shaped, glacially eroded valleys with thick alluvial fills blanketing the valley floor. Spectroscopic observations identified organic sulfur phases in suspended river sediment, floodplain deposits, and vegetation. Mass balance calculations quantified the organic sulfur flux as less than 10% of $SO^{2–}_{4}$ export, and sediment δ 34 S values were comparable to river δ 34 S SO4 . We interpreted these isotopic and chemical patterns as reflecting differences in the availability of unweathered bedrock across the Efri Haukadalsá catchment, with V-shaped valleys having greater access to fresh sulfide-bearing minerals than alluviated U-shaped valleys; this interpretation is in contrast to one in which the elevated δ 34 S SO4 values reflect fractionation during sulfur transformations along alluvial reaches. These results validated the application of river inversion models for constraining weathering fluxes and affirmed that pyrite oxidation globally, even in the presence of river sulfur cycling, modulates the abundance of atmospheric carbon dioxide.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A data analytical approach for assessing the efficacy of Operational Technology active defenses against insider threats

In recent years, the need for Operational Technology (OT) defenses has been recognized, serving as an additional line of defense when Information Technology (IT) defenses are bypassed. This is no longer considered an uncommon possibility when dealing with advanced persistent threat (APT) actors expected to be state-sponsored and receiving insider assistance. In these extreme adversarial situations, OT defenses aim to provide another layer of defense for the system, introduced directly at the physical process level, as described by the sensors data, the system model, and control actions. Just like IT defenses, two schools of thought, i.e., passive and active defenses, have emerged to address this challenge. In active defenses, representing the focus of this paper, known signatures, synthesized based on the system's unique characteristics, are inserted into the system. In contradistinction, passive methods rely solely on observing system behavior in search of patterns of normal behavior with deviations thereof representing abnormal behavior. In their most sophisticated implementations, both passive and active defenses rely on the use of data analytics to identify the patterns and synthesize the observed and/or inserted signatures. Past research has shown that passive defenses may be bypassed by APT actors relying on data analytics and their intimate knowledge of the system to evade detection by respecting the patterns identified by the defenders. Here this manuscript explores the use of active defenses under the assumption that the attacker has privileged access to the system, including access to the system's model and sensors data. Specifically, this manuscript assesses the ability of active defenses to remain invisible to the attackers, and discusses the associated challenges that must be addressed to ensure their resiliency against APT actors.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗