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67 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Digital data provenance for the power grid based on a Keyless Infrastructure Security Solution

In this work a data provenance system for grid-oriented applications is presented. The proposed Keyless Infrastructure Security Solution (KISS) provides mechanisms to store and maintain digital data fingerprints that can later be used to validate and assert data provenance using a time-based, hash tree mechanism. The developed solution has been designed to satisfy the stringent requirements of the modern power grid including execution time and storage necessities. Its applicability has been tested using a lab-scale, proof-of-concept deployment that secures an energy management system against the attack sequence observed on the 2016 Ukrainian power grid cyberattack. The results demonstrate a strong potential for enabling data provenance in a wide array of applications, including speed-sensitive applications such as those found in control room environments.

Sebastian Cardenas, David J.↗
DOE OSTI2026

Feature Engineering and Ensemble Methods for Imbalanced ICS Intrusion Detection: Pipeline Audit and Constrained Evaluation

Industries are becoming increasingly connected and are more vulnerable to cyberattacks due to the widened attack surface. Industrial Control Systems (ICS) are among the most critical sectors that malicious actors can target, as such attacks can cause significant operational disruption and physical damage. It is imperative to detect such attacks as early as possible. This paper evaluates constraint-conditioned optimistic performance estimates for traditional ML models in ICS intrusion detection (i.e., estimates obtained under contiguous, non-shuffled temporal evaluation without test-set alteration, but with pre-split feature engineering that may introduce temporal leakage, due to dataset constraints). Our findings are threefold. First, we quantify how iterative feature engineering affects tree-based ensemble performance and examine how pipeline decisions (split strategy, sampling scope, and cleaning policy) can inflate or reduce reported IDS results under constraint-bound evaluation. Second, we compare intrinsic class-imbalance handling across ensemble models. Third, under our current pipeline constraints (including pre-split feature engineering), CatBoost achieves the best performance on Water Storage Tank (accuracy: 0.9831, class-1 F1: 0.9682), while Light- GBM achieves the best performance on Gas Pipeline (accuracy: 0.9618, class-1 F1: 0.9086).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Application of Multi-Criteria Decision Analysis Techniques for Informing Select Agent Designation and Decision Making

The Centers for Disease Control and Prevention (CDC) Select Agent Program establishes a list of biological agents and toxins that potentially threaten public health and safety, the procedures governing the possession, utilization, and transfer of those agents, and training requirements for entities working with them. Every 2 years the Program reviews the select agent list, utilizing subject matter expert (SME) assessments to rank the agents. In this study, we explore the applicability of multi-criteria decision analysis (MCDA) techniques and logic tree analysis to support the CDC Select Agent Program biennial review process, applying the approach broadly to include non-select agents to evaluate its generality. We conducted a literature search for over 70 pathogens against 15 criteria for assessing public health and bioterrorism risk and documented the findings for archiving. The most prominent data gaps were found for aerosol stability and human infectious dose by inhalation and ingestion routes. Technical review of published data and associated scoring recommendations by pathogen-specific SMEs was found to be critical for accuracy, particularly for pathogens with very few known cases, or where proxy data (e.g., from animal models or similar organisms) were used to address data gaps. Analysis of results obtained from a two-dimensional plot of weighted scores for difficulty of attack (i.e., exposure and production criteria) vs. consequences of an attack (i.e., consequence and mitigation criteria) provided greater fidelity for understanding agent placement compared to a 1-to-n ranking and was used to define a region in the upper right-hand quadrant for identifying pathogens for consideration as select agents. A sensitivity analysis varied the numerical weights attributed to various properties of the pathogens to identify potential quantitative (x and y) thresholds for classifying select agents. The results indicate while there is some clustering of agent scores to suggest thresholds, there are still pathogens that score close to any threshold, suggesting that thresholding “by eye” may not be sufficient. The sensitivity analysis indicates quantitative thresholds are plausible, and there is good agreement of the analytical results with select agent designations. A second analytical approach that applied the data using a logic tree format to rule out pathogens for consideration as select agents arrived at similar conclusions.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2016

Fir Decline and Mortality in the Southern Siberian Mountains

Increased dieback and mortality of dark needle conifer (DNC) stands (composed of fir (Abies sibirica),Siberian pine (Pinus sibirica) and spruce (Picea obovata))were documented in Russia during recent decades. Here we analyzed spatial and temporal patterns of fir decline and mortality in the southern Siberian Mountains based on satellite, in situ and dendrochronological data. The studied stands are located within the boundary between DNC taiga to the north and forest-steppe to the south. Fir decline and mortality were observed to originate where topographic features contributed to maximal water-stress risk, i.e., steep (1825),convex, south-facing slopes with a shallow well-drained root zone. Fir regeneration survived droughts and increased stem radial growth, while upper canopy trees died. Tree ring width(TRW) growth negatively correlated with vapor pressure deficit (VPD), drought index and occurrence of late frosts, and positively with soil water content. Previous year growth conditions (i.e., drought index, VPD, soil water anomalies)have a high impact on current TRW (r 0.600.74). Fir mortality was induced by increased water stress and severe droughts (as a primary factor) in synergy with bark-beetles and fungi attacks (as secondary factors). Dendrochronology data indicated that fir mortality is a periodic process. In a future climate with increased aridity and drought frequency, fir (and Siberian pine) may disappear from portions of its current range (primarily within the boundary with the forest steppe)and is likely to be replaced by drought-tolerant species such as Pinus sylvestris and Larix sibirica.

Kharuk, Viacheslav I.↗
NASA NTRS1986

Constructing a working taxonomy of functional Ada software components for real-time embedded system applications

A major impediment to a systematic attack on Ada software reusability is the lack of an effective taxonomy for software component functions. The scope of all possible applications of Ada software is considered too great to allow the practical development of a working taxonomy. Instead, for the purposes herein, the scope of Ada software application is limited to device and subsystem control in real-time embedded systems. A functional approach is taken in constructing the taxonomy tree for identified Ada domain. The use of modular software functions as a starting point fits well with the object oriented programming philosophy of Ada. Examples of the types of functions represented within the working taxonomy are real time kernels, interrupt service routines, synchronization and message passing, data conversion, digital filtering and signal conditioning, and device control. The constructed taxonomy is proposed as a framework from which a need analysis can be performed to reveal voids in current Ada real-time embedded programming efforts for Space Station.

Wallace, Robert↗
DOE OSTI2019

Mixed Integer Nonlinear Programming Approaches to Enhance Resiliency and Response Strategies in Critical Infrastructure

Motivation. Critical infrastructures are large, complex engineered systems that must be operated robustly under abnormal conditions resulting from natural hazards or intentional acts. For example, electric power systems must be robust to line faults, water utilities must rapidly mitigate contamination incidents, and computing networks must adapt to adversarial intrusions to protect critical information. Problem. It is difficult for decision-makers within resiliency analysis in critical infrastructure to optimize designs and develop effective response strategies that can account for uncertainties. Facing incomplete information and the sheer scope that a natural hazard or attack vector may incorporate, response can be ineffective without reliable, scalable decision support tools. These problems are intrinsically nonlinear and involve discrete decisions, and unfortunately, existing off-the-shelf mathematical programming methods cannot support optimization-based decision-making of these nonlinear at scale. Method/Approach and Results. This project emphasized development of fundamental optimization strategies that supported real- time mitigation and response for critical infrastructures. In particular, the project developed multi- tree approaches based on piecewise outer-approximations for solution of mixed-integer nonlinear programming (MINLP) problems. These techniques alternate between an MILP or MISOCP relaxation to obtain a lower bound and candidate discrete solutions and an NLP subproblem to obtain upper bounds. Using tailored relaxations based on problem structure, these methods were used to solve several key applications in resilience and response of critical infrastructure. This work resulted in two open-source, copyrighted software packages: CORAMIN (https://github.com/Coramin/Coramin) -- an object-oriented mathematical programming framework that supports tailored multi-tree algorithms for solution of large- scale mixed-integer nonlinear programming; and EGRET (Electrical Grid Research and Engineering Toolkit) (https://github.com/grid- parity-exchange/Egret) -- a declarative mathematical programming framework built upon CORAMIN and Pyomo for formulation and solution of resilience and operations problems in power grid systems. Furthermore, these tools resulted in several important published results, including the following: The first known global optimization approach that could solve the unit-commitment problem with nonlinear power flow constraints on medium-sized test problems; Improved parallel optimization-based bounds tightening and strengthening of relaxations of AC power flow constraints; and, Optimization-based approaches for improved grid resilience and use of demand response to improve grid resilience with reduction in capital requirements. Result Implications. This project developed first-of-a-kind algorithms for decision-making in critical infrastructure resilience operations and planning, as well as a next-generation toolkit for MINLP researchers. These approaches leveraged high-performance computing architectures to solve some of the largest, most challenging nonlinear discrete optimization problems to global optimality, and these successes were captured in open-source software to enable optimization-based decision-making, and efficient solution of MINLP formulations for electric power transmission grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

The role of nutrients in drought‐induced tree mortality and recovery

Summary Global forests are experiencing rising temperatures and more severe droughts, with consistently dire forecasts for negative future impacts. Current research on the physiological mechanisms underlying drought impacts is focused on the water‐ and carbon‐associated mechanisms. The role of nutrients is notably missing from this research agenda. Here, we investigate what role, if any, forest nutrition plays for survival and recovery of forests during and after drought. High nutrient availability may play a detrimental role in drought survival due to preferential biomass allocation aboveground that (1) predispose plants to hydraulic constraints limiting photosynthesis and promoting hydraulic failure, (2) increases carbon costs during periods of carbon starvation, and (3) promote biotic attack due to low tissue carbon: nitrogen (C : N). When nutrient uptake occurs during drought, high nutrient availability can increase water use efficiency thus minimizing negative feedbacks between carbon and nutrient balance. Nutrients are released after drought ceases, which might promote faster recovery but the temporal dynamics of microbial immobilization and nutrient leaching have a significant impact on nutrient availability. We provide a framework for understanding nutrient impacts on drought survival that allows a more complete analysis of forest ecosystem responses. Contents Summary 513 I. Introduction 513 II. Integrating nutrients into the hydraulic framework predicting mechanisms of drought survival, mortality, and recovery 514 III. Integration 517 Acknowledgements 518 References 518

Gessler, Arthur↗
DOE OSTI2026

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗
NASA NTRS2015

Climate-Induced Mortality of Spruce Stands in Belarus

The aim of this work is an analysis of the causes of spruce (Picea abies L.) decline and mortality in Belarus. The analysis was based on forest inventory and Landsat satellite (land cover classification, climate variables (air temperature, precipitation, evaporation, vapor pressure deficit, SPEI drought index)), and GRACE-derived soil moisture estimation (equivalent of water thickness anomalies, EWTA). We found a difference in spatial patterns between dead stands and all stands (i.e., before mortality). Dead stands were located preferentially on relief features with higher water stress risk (i.e., higher elevations, steeper slopes, south and southwestern exposure). Spruce mortality followed a series of repeated droughts between 1990 and 2010. Mortality was negatively correlated with air humidity (r = -0.52), and precipitation (r = -0.57), and positively correlated with the prior year vapor pressure deficit (r = 0.47), and drought increase (r = 0.57). Mortality increased with the increase in occurrence of spring frosts (r = 0.5), and decreased with an increase in winter cloud cover (r = -0.37). Spruce mortality was negatively correlated with snow water accumulation (r = -0.81) and previous year anomalies in water soil content (r = -0.8). Weakened by water stress, spruce stands were attacked by pests and phytopathogens. Overall, spruce mortality in Belarussian forests was caused by drought episodes and drought increase in synergy with pest and phytopathogen attacks. Vast Picea abies mortality in Belarus and adjacent areas of Russia and Eastern Europe is a result of low adaptation of that species to increased drought. This indicates the necessity of spruce replacement by drought-tolerant indigenous (e.g., Pinus sylvestris, Querqus robur) or introduced (e.g., Larix sp. or Pseudotsuga menzieslii) species to obtain sustainable forest growth management.

spruce decline↗
NASA NTRS1991

Systematic methods for knowledge acquisition and expert system development

Nine cooperating rule-based systems, collectively called AUTOCREW which were designed to automate functions and decisions associated with a combat aircraft's subsystems, are discussed. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base and to assess the cooperation between the rule bases. Simulation and comparative workload results for two mission scenarios are given. The scenarios are inbound surface-to-air-missile attack on the aircraft and pilot incapacitation. The methodology used to develop the AUTOCREW knowledge bases is summarized. Issues involved in designing the navigation sensor selection expert in AUTOCREW's NAVIGATOR knowledge base are discussed in detail. The performance of seven navigation systems aiding a medium-accuracy INS was investigated using Kalman filter covariance analyses. A navigation sensor management (NSM) expert system was formulated from covariance simulation data using the analysis of variance (ANOVA) method and the ID3 algorithm. ANOVA results show that statistically different position accuracies are obtained when different navaids are used, the number of navaids aiding the INS is varied, the aircraft's trajectory is varied, and the performance history is varied. The ID3 algorithm determines the NSM expert's classification rules in the form of decision trees. The performance of these decision trees was assessed on two arbitrary trajectories, and the results demonstrate that the NSM expert adapts to new situations and provides reasonable estimates of the expected hybrid performance.

Belkin, Brenda L.↗
DOE OSTI2018

Optimal Black Start Allocation for Power System Restoration

Equipment failures, operator errors, natural disasters and cyber-attacks can and have caused extended blackouts of the electric grid. Even though such events are rare, preparedness for them is critical because extended power outages endanger human lives, compromise national security, or result in economic losses of billions of dollars. Since most of the generating units cannot restart without connecting to an energized grid, the system operator relies on a few units with the ability to start autonomously, called Black Start (BS) units, to restore the power system. Allocating and maintaining these units is costly and can severely impact the restoration security and time. We formulate an optimization problem to optimally allocate BS units in the grid, while simultaneously optimizing over the restoration sequence. We extend existing optimal allocation models by including grid considerations such as active power nodal balance, transmission switching, nodal reactive power support and voltage limits. In order to aid the branch and bound tree that solves the resulting large scale mixed integer program, we propose a randomized heuristic that is executed multiple times in parallel on a high-performance computing environment to find feasible solutions. Here, we proceed to solve the IEEE-39, the IEEE-118, and a simplified WECC system with 225 nodes and 136 generators to near optimality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Nuclear Power Plant Cyber Security Discrete Dynamic Event Tree Analysis (LDRD 17-0958) FY17 Report

Instrumentation and control of nuclear power is transforming from analog to modern digital assets. These control systems perform key safety and security functions. This transformation is occurring in new plant designs as well as in the existing fleet of plants as the operation of those plants is extended to 60 years. This transformation introduces new and unknown issues involving both digital asset induced safety issues and security issues. Traditional nuclear power risk assessment tools and cyber security assessment methods have not been modified or developed to address the unique nature of cyber failure modes and of cyber security threat vulnerabilities. iii This Lab-Directed Research and Development project has developed a dynamic cyber-risk in- formed tool to facilitate the analysis of unique cyber failure modes and the time sequencing of cyber faults, both malicious and non-malicious, and impose those cyber exploits and cyber faults onto a nuclear power plant accident sequence simulator code to assess how cyber exploits and cyber faults could interact with a plants digital instrumentation and control (DI&C) system and defeat or circumvent a plants cyber security controls. This was achieved by coupling an existing Sandia National Laboratories nuclear accident dynamic simulator code with a cyber emulytics code to demonstrate real-time simulation of cyber exploits and their impact on automatic DI&C responses. Studying such potential time-sequenced cyber-attacks and their risks (i.e., the associated impact and the associated degree of difficulty to achieve the attack vector) on accident management establishes a technical risk informed framework for developing effective cyber security controls for nuclear power.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Close and distant: Contrasting the metabolism of two closely related subspecies of Scots pine under the effects of folivory and summer drought

The metabolome, the chemical phenotype of an organism, should be shaped by evolution. Metabolomes depend on genetic composition and expression, which can be sources of evolutionary inertia, so most aspects of metabolomes should be similar in closely related sympatric species. We examined the metabolomes of two sympatric subspecies of Pinus sylvestris in Sierra Nevada (southern Iberian Peninsula), one introduced (ssp. iberica) and one autochthonous (ssp. nevadensis), in summer and winter and exposed to folivory by the pine processionary moth. The overall metabolomes differed between the subspecies but both tended to respond more similarly to folivory. The metabolomes of the subspecies were more dissimilar in summer than in winter, and iberica trees had higher concentrations of metabolites directly related to drought stress. Our results suggest that certain plant metabolic responses associated with folivory have been conserved throughout evolutionary history. The larger divergence between subspecies metabolomes in summer is likely due to the warmer and drier conditions that the northern iberica subspecies experience in Sierra Nevada. Our results provide crucial insights into how iberica populations would respond to the predicted conditions of climate change under an increased defoliation, two recent severe issues in the Mediterranean Basin.

54 ENVIRONMENTAL SCIENCES↗