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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Modeling Cyber Supply Chain Incidents with Multilayered Graph Motifs

As noted within the literature, supply chain includes people and organizations---manufacturers, integrators, and third-party vendors---that are involved in one or more stages of a product lifecycle. Since supply chains, by definition, include organizations and people, supply chain risk management activities must consider dependencies between an organization's business processes and third-party resources. Just as adversarial tactics can be implemented via techniques implemented via networked computer systems, so can such tactics be expressed via legal business relationships. A cyber incident may have an exponential impact downstream, for example, by leveraging a product's distribution channel (e.g. malicious updates in SolarWinds, buggy updates in CrowdStrike). Similarly, legitimate and legal business relationships also affect the attack surface exposure of systems, enabling long-term persistence and/or unknown impacts to product quality that are hard to detect. This paper catalogs several recent digital supply chain incidents and applies a multilayered network formalism to develop structural indicators (graph motifs) that reflect potentially-adversarial behavior. Finally, we compare and contrast the characteristics of adversarial tactics (e.g. Loss of Availability, Data Collection) that leverage cyber-physical dependencies to those that leverage legal organizational relationships.

97 - MATHEMATICS AND COMPUTING↗

Physical & Cyber Security Modeling Interfacing Through Dante and ARCADE

Physical security is increasingly facing new threats from cyber attackers, for which there is little research in the way of characterizing this threat. This report discusses the efforts to combine cyber and physical security modeling tools to investigate this novel combinatorial threat space. To accomplish this, the Dante force-on-force modeling and simulation software and the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) were integrated. Dante provides a 3D environment which models the physical world, while ARCADE provides the cyber and control systems world.

42 ENGINEERING↗

Defensive Cybersecurity Architecture Design Using Force-on-Force Cyber-Physical Modeling

Currently, nuclear power plant physical security systems are highly dependent on air-gaps as a protective measure against cyber-threats. Cyber-physical threats become more likely as advanced cyber-threat capabilities to jump air-gaps transition into common use. Defending against the emerging threat of cyber-enabled physical intrusions is poorly understood. The consequence of these cyber-physical attacks has no quantitative analysis method to inform risk-informed, performance-based cybersecurity approaches. By modifying the physical security simulation tool Dante, cyber-physical threat consequence was able to be analyzed on a notional facility. The results of this analysis are used to design a Defensive Cybersecurity Architecture (DCSA) for the physical security system to produce example resilience measures for this notional facility. A DCSA defines security levels to provide a graded approach for defending plant functions, and security zones for trusted communication between systems. This approach can be applied to real world systems to produce physical protection systems and response measures that are resilient to cyber-physical threats.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Modeling Communication Infrastructures of Cyber Physical Systems

This effort explores modeling cyber infrastructure, including communication devices like switches, routers, sensors, and controllers, and physical media attributes like propagation of radio signals, in coordination with power distribution system model layouts. To do this, the project studies real-world configurations to define axioms of how different communication media is deployed with control equipment. These axioms will be used to develop tools to generate realistic cyber infrastructure models from starting power system models. This effort leverages and builds on the co-simulation platform developed by the other RD2C projects. The axioms and tools will be validated and demonstrated with the NS3 simulation tool as part of a co-simulation to show the behavior/impacts of cyber infrastructure on control operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Mission Assurance Modeling and Simulation: A Cyber Security Roadmap

This paper proposes a cyber security modeling and simulation roadmap to enhance mission assurance governance and establish risk reduction processes within constrained budgets. The term mission assurance stems from risk management work by Carnegie Mellon's Software Engineering Institute in the late 19905. By 2010, the Defense Information Systems Agency revised its cyber strategy and established the Program Executive Officer-Mission Assurance. This highlights a shift from simply protecting data to balancing risk and begins a necessary dialogue to establish a cyber security roadmap. The Military Operations Research Society has recommended a cyber community of practice, recognizing there are too few professionals having both cyber and analytic experience. The authors characterize the limited body of knowledge in this symbiotic relationship. This paper identifies operational and research requirements for mission assurance M&S supporting defense and homeland security. M&S techniques are needed for enterprise oversight of cyber investments, test and evaluation, policy, training, and analysis.

Gendron, Gerald↗

Development of alternative data analysis techniques for improving the accuracy and specificity of natural resource inventories made with digital remote sensing data

An investigation was conducted into ways to improve the involvement of state and local user personnel in the digital image analysis process by isolating those elements of the analysis process which require extensive involvement by field personnel and providing means for performing those activities apart from a computer facility. In this way, the analysis procedure can be converted from a centralized activity focused on a computer facility to a distributed activity in which users can interact with the data at the field office level or in the field itself. A general image processing software was developed on the University of Minnesota computer system (Control Data Cyber models 172 and 74). The use of color hardcopy image data as a primary medium in supervised training procedures was investigated and digital display equipment and a coordinate digitizer were procured.

Lillesand, T. M.↗

Ocean modelling on the CYBER 205 at GFDL

At the Geophysical Fluid Dynamics Laboratory, research is carried out for the purpose of understanding various aspects of climate, such as its variability, predictability, stability and sensitivity. The atmosphere and oceans are modelled mathematically and their phenomenology studied by computer simulation methods. The present state-of-the-art in the computer simulation of large scale oceans on the CYBER 205 is discussed. While atmospheric modelling differs in some aspects, the basic approach used is similar. The equations of the ocean model are presented along with a short description of the numerical techniques used to find their solution. Computational considerations and a typical solution are presented in section 4.

Cox, M.↗

A real-time distributed solid oxide electrolysis cell (SOEC) model for cyber-physical simulation

System integration and dynamic operability between SOEC and balance-of-plant (BoP) components are major technical challenges before realizing rapid load following of SOEC systems. Cyber-physical simulation (CPS) is a leading-edge digital engineering approach and is regarded as the next step beyond Digital Twins. CPS approach can be used to research SOEC system integration and develop dynamic controls prior to actual pilot testing without using a real SOEC. To seamlessly couple with BoP hardware and access non-observable operational parameters (e.g., local temperature gradient) during transients, a distributed one-dimensional (1D) real-time SOEC model was developed. Its real-time execution was demonstrated for 20 to 640 nodes at the fixed time step of 5 ms. A higher excess air ratio enabled smaller local temperature gradients on SOEC solid materials and faster transients upon current density step change from 0.15 to 0.55 A cm -2 . During the transients, the magnitude of the peak temperature gradient nearly doubled in 10 s from -3.5 to -5.9 °C cm -1 . This represents a significant operating risk that can impact the dynamic operability of SOEC systems. In addition, the local temperature gradient was found to change directions on all nodes in SOEC solid materials, with the greatest impact on the upstream nodes. The SOEC model was also tested at the thermal neutral voltage using actual process air flow parameters as variable model inputs. Variable process air temperatures were found to induce alternating local temperature gradients on SOEC solid materials. These are new operational mechanisms for SOEC degradation relevant for load following operational modes yet distinct from previous reports. To mitigate these unfavorable features, the SOEC can be operated at voltages that are slightly (±20 mV) deviated from the thermal neutral voltage. Here, the corresponding net thermal energy change was less than 1.6% of the electric power consumption. This 1D real-time SOEC model established the basis of cyber-physical simulation of SOEC hybrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Cybersecurity Enhancement in Digital Substations: Hidden Markov Model-Based Smart Cyber Switching and Threat Response

The rising incidence of cyber-attacks on critical infrastructure and power grids poses significant threats to the stability and reliability of electrical substations, with potentially devastating consequences such as extended blackouts. This paper introduces an advanced cybersecurity framework aimed at safeguarding IEC 61850-based substations through the integration of software-defined networking (SDN) and digital twin (DT) technologies. The proposed DT-based framework employs smart cyber switching (SCS) for proactive threat mitigation and concurrent intelligent electronic device (CIED) for swift system restoration, thereby maintaining continuous operational integrity and robust cybersecurity defenses. Central to this framework is the adaptive port controller (APC), which enables dynamic port management to adapt to evolving threats, and an intrusion detection system (IDS) designed to detect and neutralize malicious attacks on IEC 61850-based sampled value (SV) and generic object-oriented substation event (GOOSE) messages within the substation’s communication network. Further, novel predictive intrusion detection and response (PIDR) algorithm is implemented on a digital substation (DS) to predict the best route to be taken by the attacker. The efficacy of these comprehensive cybersecurity frameworks is validated through rigorous simulations and a hardware-in-the-loop (HIL) testbed, showcasing the system’s ability to sustain substation operations amidst cyber-attacks.

Digital substation↗

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

MBSE↗

Internship Presentation: Integrating Safety and Cybersecurity: Security-by-Design with SOWT Analysis for Reactor Testing

This study covers leveraging reactor testing facilities that are primarily designed with a focus on safety to enhance cybersecurity testing. By incorporating reactor security-by-design with reactor safety-by-design principles and adopting defense-in-depth strategies that emphasize both safety and security, the research evaluates applicable cyber tools, models, and solutions. This includes simulating specific cyber-attack scenarios using reactor simulators and performing SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis to improve the cybersecurity of reactor systems.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Developing Deep Learning Models for System Remaining Useful Life Predictions: Application to Aircraft Engines

Prognostics and health management (PHM) is an important part of ensuring reliable operations of complex safety- critical systems. System-level remaining useful life (RUL) estimation is a much more complex problem than making estimations at the component level, and system-level RUL methodologies remain sparse in the literature. Model-based approaches have traditionally worked in the past for components such as capacitors, MOSFETs, batteries, or hard-drives (to name a few examples), but developing high fidelity dynamics models of cyber physical systems that can be used to study the effects of multiple degrading components in the system remains a challenging task. Some initial work on model-based System RUL predictions was demonstrated in Khorasgani, et al [1], but, to generalize the system-level prognostics problem, we have to resort to pure data driven and hybrid approaches. In this work, we propose an end-to-end data- driven framework for developing deep learning models to predict remaining useful life of cyber physical systems operating under unknown faulty conditions. The raw data is organized with a data schema that improves the model development process and down stream data analysis tasks. Due to the unknown faulty conditions, the raw sensor data is transformed into signals that expose the underlying degradation processes, which are then used for model development. Bayesian Optimization is used to tune the model parameters prior to training and validation. We show that this approach results in accurate predictions within 3 cycles to end of life (EOL). We demonstrate the effectiveness of our approach by applying it to the N-CMAPSS turbofan engine dataset recently released by NASA, which includes high fidelity degradation modeling, real world operating conditions, and a large set of fault operating modes.

Prognostics↗

Model Development Highlight for 1984: The GLA Fourth Order GCM

A number of improvements have been made to the GLA Fourth Order General Circulation Model and its associated run procedures during the past year. Major development efforts have been carried out in the following areas: (1) model resolution; (2) boundary fields and topography; (3) post-processing of model results on CYBER computer; and (4) model source code.

Pfaendtner, J.↗

Bridging the Gap Between Requirements and Model Analysis: Evaluation on Cyber-Physical Challenge Problems

We present a framework for introducing high-level requirement specifications in the automated analysis of dataflow models. By integrating the FRET requirements elicitation tool with the CoCoSim analyzer, our framework enables the analysis of hierarchical Simulink models against requirements written in a restricted English language. More precisely, we support: automatic extraction of Simulink model information and association of high-level requirements with target model signals and components; translation of temporal logic formulas into synchronous dataflow CoCoSpec specifications as well as Simulink monitors; and interpretation of counterexamples produced by the analysis both at the requirement and model level. The features provided by our framework are generic and can be used to integrate other requirements elicitation and Simulink/Lustre analysis tools. We report on the lessons learned from the application of our approach to the Lockheed Martin Cyber-Physical, aerospace-inspired challenge problems. For the analysis, we used the Kind2, Zustre, and Simulink Design Verifier (SLDV) tools.

Simulink↗

Algorithms for solving large sparse systems of simultaneous linear equations on vector processors

Very efficient algorithms for solving large sparse systems of simultaneous linear equations have been developed for serial processing computers. These involve a reordering of matrix rows and columns in order to obtain a near triangular pattern of nonzero elements. Then an LU factorization is developed to represent the matrix inverse in terms of a sequence of elementary Gaussian eliminations, or pivots. In this paper it is shown how these algorithms are adapted for efficient implementation on vector processors. Results obtained on the CYBER 200 Model 205 are presented for a series of large test problems which show the comparative advantages of the triangularization and vector processing algorithms.

David, R. E.↗