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DOE OSTI2017

Chrysler Upset Protrusion Joining Techniques for Joining Dissimilar Metals

The project goal was to develop and demonstrate a robust, cost effective, and versatile joining technique, known as Upset Protrusion Joining (UPJ), for joining challenging dissimilar metal com-binations, especially those where one of the metals is a die cast magnesium (Mg) component. Since two of the key obstacles preventing more widespread use of light metals (especially in high volume automotive applications) are 1) a lack of robust joining techniques and 2) susceptibility to galvanic corrosion, and since the majority of the joint combinations evaluated in this project include die cast Mg (the lightest structural metal) as one of the two materials being joined, and since die casting is the most common and cost effective process for producing Mg components, then successful project completion provides a key enabler to high volume application of lightweight materials, thus potentially leading to reduced costs, and encouraging implementation of lightweight multi-material vehicles for significant reductions in energy consumption and reduced greenhouse gas emissions. Eco-nomic benefits to end-use consumers are achieved primarily via the reduction in fuel consumption. Unlike currently available commercial processes, the UPJ process relies on a very robust mechanical joint rather than intermetallic bonding, so the more cathodic material can be coated prior to joining, thus creating a robust isolation against galvanic attack on the more anodic material. Additionally, since the UPJ protrusion is going through a hole that can be pre-drilled or pre-punched prior to coating, the UPJ process is less likely to damage the coating when the joint is being made. Further-more, since there is no additional cathodic material (such as a steel fastener) used to create the joint, there is no joining induced galvanic activity beyond that of the two parent materials. In accordance with its originally proposed plan, this project has successfully developed process variants of UPJ to enable joining of Mg die castings to aluminum (Al) and steel sheet components of various thicknesses, strengths and coating configurations. While most development focused on the simpler round boss version of the process, an additional phase of the work focused on devel-opment of an oval boss version to support applications with narrow flanges, while yet another vari-ant of the process, known as Upset Cast Riveting (UCR), was developed and evaluated for joining mixed metals that may not necessarily include Mg or Al die cast components. Although each varia-tion posed unique challenges described later in the report, all variations were successfully produced and evaluated, and each could be further developed for specific types of commercial applications. In this project, UPJ performed favorably against the benchmark self-pierce riveting (SPR) process in Mg AM60B to Al 6013 combinations although significant corrosion challenges were observed in both processes, especially for the bare Mg to bare Al configurations. Additional challenges were observed in joining Mg to steel with the UPJ process (SPR was not evaluated for this combination as it was not considered viable). To pass FCA’s specified corrosion tests with Mg/steel combina-tions, new steel treatments were evaluated, as well as adhesives and sealed edges. These showed significant improvement. In general, UPJ performed very well in Mg to Al 6016 combinations, even in corrosion evaluation of the bare Mg to bare Al configuration (again, SPR was not evaluated for this material combination as the 1.1 mm thick Al6016 sheet thickness was considered too thin for the SPR process). The improvement in corrosion performance of the Mg to Al 6016 combina-tion over the Mg to Al 6013 combination was thought to be a result of the lower copper content in the Al 6016 alloy. Oval boss joints showed substantial improvement in all joint strength criteria compared to 8.0-mm diameter round boss joints but were not evaluated for corrosion performance. The improved joint strength is likely a result of larger shear area. Cosmetic corrosion performance of all test assemblies (UPJ, UCR and SPR) was a challenge due to exposed edges and crevices al-lowing undercutting of the coatings. In real world component applications, the exposed edges, so prevalent on the joining test coupons, would be less prevalent and easier to protect.

36 MATERIALS SCIENCE↗

DOE OSTI2014

PMU Data Integrity Evaluation through Analytics on a Virtual Test-Bed

Power systems are rapidly becoming populated by phasor measurement units (PMUs) in ever increasing numbers. PMUs are critical components of today s energy management systems, designed to enable near real-time wide area monitoring and control of the electric power system. They are able to measure highly accurate bus voltage phasors as well as branch current phasors incident to the buses at which PMUs are equipped. Synchrophasor data is used for applications varying from state estimation, islanding control, identifying outages, voltage stability detection and correction, disturbance recording, and others. However, PMU-measured readings may suffer from errors due to meter biases or drifts, incorrect configurations, or even cyber-attacks. Furthermore, the testing of early PMUs showed a large disparity between the reported values from PMUs provided by different manufacturers, particularly when frequency was off-nominal, during dynamic events, and when harmonic/inter-harmonic content was present. Detection and identification of PMU gross measurement errors are thus crucial in maintaining highly accurate phasor readings throughout the system. In this paper, we present our work in conducting analytics to determine the trustworthiness and worth of the PMU readings collected across an electric network system. By implementing the IEEE 118 bus test case on a virtual test bed (VTB) , we are able to emulate PMU readings (bus voltage and branch current phasors in addition to bus frequencies) under normal and abnormal conditions using (virtual) PMU sensors deployed across major substations in the network. We emulate a variety of failures such as bus, line, transformer, generator, and/or load failures. Data analytics on the voltage phase angles and frequencies collected from the PMUs show that specious (or compromised) PMU device(s) can be identified through abnormal behaviour by comparing the trend of its frequency and phase angle reading with the ensemble of all other PMU readings in the network. If the reading trend of a particular PMU deviates from the weighted average of the reading trends of other PMUs at nearby substations, then it is likely that the PMU is malfunctioning. We assign a weight to each PMU denoting how electric-topology-wise close it is from where the PMU under consideration is located. The closer a PMU is, the higher the weight it has. To compute the closeness between two nodes in the power network, we employ a form of the resistance distance metric. It computes the electrical distance by taking into consideration the underlying topology as well as the physical laws that govern the electrical connections or flows between the network components. The detection accuracy of erroneous PMUs should be improved by employing this metric. We present results to validate the proposed approach. We also discuss the effectiveness of using an end-to-end VTB approach that allows us to investigate different types of failures and their responses as seen by the ensemble of PMUs. The collected data on certain types of events may be amenable to certain types of analysis (e.g., alerting for sudden changes can be done on a small window of data) and hence determine the data analytics architectures is required to evaluate the streaming PMU data.

and data analytics architecture.↗

DOE OSTI2017

Software Quality Assurance for LeachXS/ORCHESTRA as a Tool for Assessment of Waste Management Systems Performance - 17486

Qualified modeling and simulation tools and experimental data are needed to provide a reasonable basis for the incorporation of realistic wasteform retention assumptions (i.e., those without orders-of-magnitude conservatism) into performance assessments and regulatory decisions. Use of highly conservative assumptions in performance assessments has historically led to the overprediction of release and near-field transport by as much as 4- to 6-orders of magnitude thereby limiting the nature and quantities of certain contaminants of concern in near surface disposal facilities. This project provides peer-reviewed models and characterization methods to provide more reasonable assumptions for use in performance assessments and regulatory decisions. Simulations tools have been developed to predict hydraulic and chemical performance of waste-forms and barriers used in nuclear applications under several important aging and degradation scenarios, including sulfate attack, carbonation, oxidation, cracking, and leaching; these tools are complaint with DOE Order 414.1D and ASME NQA-1. Wasteform characterization methods have been developed that are consistent with US EPA's Leaching Environmental Assessment Framework (LEAF) currently part of EPA's Hazardous Waste Test Methods (SW-846); the resulting experimental data are evaluated using LeachXS. ORCHESTRA models, that can be called seamlessly from LeachXS, have been developed representing both laboratory and field conditions; these models have undergone an extensive Software Quality Assurance process where they have been calibrated (where necessary), verified, and validated to be compliant with relevant guidelines. The models used for field predictions have also been incorporated into the Cementitious Barriers Partnership (CBP) Software Toolbox that allows probabilistic evaluation of field scenarios. The foci over the next year will be on providing 1) a mechanistic basis for projecting the retention of Tc-99, I-129, and other important radionuclides in near-surface disposal facilities at the Savannah River and Hanford Sites and 2) a technical basis for assessing the efficacy of macro-encapsulation of mercury-contaminated debris at the Oak Ridge Reservation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Augmented Monitoring and Condition Assessment Program for SNF Wet Storage Life Extension - 20489

Approximately 27 MTHM of spent nuclear fuel (SNF) owned and managed by the U.S. Department of Energy, Office of Environmental Management is stored in the L Basin at the Savannah River Site (SRS). This 'DOE SNF' is comprised of approximately 12,000 aluminum-clad, aluminum-based fuel assemblies (∼7 MTHM), and approximately 2000 non-aluminum fuel assemblies (∼20 MTHM). A program is in progress to perform Non-Destructive Examination (NDE) of the fuel and their storage containers to characterize the materials' condition, and to evaluate the effects of service to enable continued safe wet storage of the SNF. The Augmented Monitoring and Condition Assessment Program (AMCAP), a two-part program to develop and implement remote underwater Non-Destructive Examination of the aluminum SNF, and of the containers of the non-aluminum SNF, respectively, is aimed at the characterization and evaluation of corrosion degradation of aluminum fuel and container materials. The predominant design of the aluminum SNF (ASNF) stored in L Basin is the Materials Test Reactor (MTR) equivalent design, a plate fuel design. These SNF are stored in 5'' diameter tubes or 5'' x 5'' squares (called bundles) that are nominally 12' or up to 14' long. The SNF is de-bundled and inspected using a custom-designed MTR Fuel Inspection Table. The inspection table provides for indexed fuel positioning for a video camera examination with controlled lighting. A total of 10 of the SNF originating from foreign research and test reactors were selected for examination based on burnup, enrichment, and prior damage caused by service/storage history. A special inspection campaign of these 10 assemblies is in progress. The observed corrosion damage included minor to moderate attack from general corrosion, pitting, crevice, end grain and galvanic corrosion. Example results from the completed inspections are shown and discussed. The focus is a comparison of the as-received condition versus the as-found current storage condition that will serve to validate Water Chemistry and Corrosion Monitoring Programs. The non-aluminum SNF (NASNF) stored in L Basin are of diverse design that includes various geometries with claddings of stainless steel, Zircaloy, and Hastelloy. The fuel core materials include uranium alloys, oxides/mixed oxides, and carbides. These SNF materials, originating from early experimental and test reactors, are in various physical forms including single fuel elements and cut pieces. The fuel is stored in L Basin in various configurations including in direct bundled storage in aluminum tubes and in isolation cans that are in the bundles or in a larger over-size storage container (OSC). Concern with inside-out corrosion and the potential loss of configuration control and ability to handle the storage containers prompted the development of remote NDE methods that include visual and UT technologies to assess the condition of the containers. Candidate stored materials were selected for a special inspection campaign; the development of the NDE methods for the inspection for galvanic, crevice and sediment-induced corrosion (inside-out) are discussed. A summary of the SNF storage in L Basin at the SRS, and an overview of the AMCAP to enable continued safe storage of DOE SNF are described. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Probabilistic Risk Assessment of Spent Fuel Pool Cooling System Failure Considering Safety and Security Initiating Events

In order to quantify the probable risk associated with a safety system, nuclear safety risk evaluation process is applied which is generally performed in three steps. The first step is to calculate the damage frequency of a critical system. This step is followed by the radioactive source term estimation due to the potential system damage. The final step is the assessment of off-site consequences. The safety risk formula is shown by Eq. (1). P{sub F} is the probability of safety system failure (the probability used describes a random, independent event), and C is the consequence value. R{sub SAF} = P{sub F} * C (1) The security risk associated with an attack on critical infrastructure and/or special nuclear materials theft is usually evaluated using three- term risk equation (probability of attack, probability of adversary success, and consequence). A security threat and the related initiating events are not considered in a pure safety risk analysis. The vulnerability of the physical protection system is performed independently even though the consequence resulting from a security initiating event can be similar to a safety related initiating event and thus gets double counted. The security risk can be calculated using Eq. (2) R{sub SEC} = P{sub A} * P{sub S} * C (2) PA is the probability of attack, P{sub S} is the probability of adversary success (P{sub S} = 1 - P{sub I} P{sub N}). P{sub I} being the probability of interruption which accounts for the probabilities of detection of all timely detection elements along an adversary path. PN being the probability of neutralization: the result of engagement of the response force with the adversaries after the interruption has occurred. C is the consequence magnitude from a successful attack. The two security probabilities do not describe random, independent events. As a result, because of the differences in the randomness and independence of the respective safety and security probabilities, the safety and the security risks are currently calculated separately. The consequence term in nuclear safety and security risk evaluation have the same definition. An effort is made here to study the effect on the overall risk by considering security initiating events along with the subsequent failure of the intermediate safety element. The target selected is a spent fuel storage pool for analyzing the public risk arising from the interplay between nuclear security and safety initiating events. EASI (Estimate of Adversary Sequence Interruption) model is used to calculate the probability of interruption related to a security system that leads to the calculation of the security initiating event frequency. Further progression of this initiating security event to a top event is analyzed using a Probabilistic Safety Assessment (PSA) tool, SAPHIRE (version 8) to obtain a joint pool damage frequency. For the progression of events leading to a top event, the failure of the intermediate safety elements is assumed to be external random events such as heavy load drop and fire events. The objectives of this study is to (1) determine the double accounting of frequency of failure, risk and allocated resources in the scenario of a non-random security initiating event leading to a safety random event chain (2) compare the damage frequency from pure security with the frequency of combined security-safety failure event and pure safety failure events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Quantum Computing and Cryptography: Analysis, Risks, and Recommendations for Decisionmakers

Some influential American policymakers, scholars, and analysts are extremely concerned with the effects that quantum computing will have on national security. Similar to the way space technology was viewed in the context of the US-Soviet rivalry in the Cold War, they view scientific advancement in quantum computing as a race with significant national security consequences and a part of the emerging US-China rivalry. It is claimed that the winner of this race will be able to thwart all the cryptographic efforts of the loser and gain unfettered access to any state secret of the losing government. Additionally, it is suggested that the winner will be able to protect their secrets with a higher level of security than contemporary cryptography guarantees at the moment. This paper argues that these three claims are considerably overstated, and that policymakers and scholars should shift focus to a different national security problem that quantum computing will create. Maintaining the long-term security of secret information secured by contemporary cryptographic protections, which will fail against an attack by a future quantum computer, is the predominant challenge needing attention. This paper takes a technically-informed approach to this issue. It first lays out the national security problems that are envisioned in much of the current discourse surrounding quantum computing. Then, it will assess the technical advantages that quantum computers will have over classical computers in the field of cryptography. Next, it will provide an explanation of the specific ways that the technical realities of quantum computing are inconsistent with the predominant areas of concern. Following, it will highlight the more pressing national security problem posed by quantum computing that the public discussion has, for the most part, missed. The piece will conclude with recommendations for how to mitigate this issue.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Enhancing Nuclear and Radiological Security in Polarized Times: Safeguarding Against Extremist Insider Threats

Domestic violent extremism has been on the rise in recent years, fueled by growing political polarization, the COVID-19 pandemic, and the spread of misinformation online. This concerning trend raises an important question: has this increase in extremist violence manifested in more incidents involving radioactive or nuclear (RN) materials and a corresponding security concern? To explore this question, we analyzed existing data on events involving chemical, biological, radiological, or nuclear materials over time. Specifically, we examined the rate of RN-related incidents, the targets of these events, and the ideologies motivating the perpetrators by using the Violent Non-State Actor Chemical, Biological, Radiological, and Nuclear Event Database from the National Consortium for the Study of Terrorism and Responses to Terrorism. Our analysis aimed to determine whether the broader rise of violent extremism has translated to an elevated risk of attacks involving RN materials. Results of the analysis revealed that there was no clear increase in events involving RN material in the dataset. However, given the rarity of these events, this conclusion does not indicate that such a trend might not appear in coming years if violent extremism continues to rise. To address the potential risk presented by violent extremism, in addition to quantifying the frequency of RN events, we also reviewed traits that could make organizations more susceptible to insider threats from radicalized employees. Focusing on the literature around counterproductive workplace behavior, we identified organizational characteristics that might increase the risk of malicious acts committed by radicalized insiders. These risk factors include abusive leadership, situational constraints, and organizational injustice. Finally, using these organizational risk characteristics, we discuss interventions that organizations with RN material can take to reduce their risk of attacks stemming from violent extremism while still protecting individual rights to privacy and civil liberties. Overall, this article provides an overview of the intersections between rising domestic extremism, insider threats, and risks posed by RN materials. We present current data on trends and patterns in this space as well as practical guidance for organizational resilience.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2014

HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems

Physical device safety is typically implemented locally using embedded controllers, while operations safety is primarily performed in control centers. Safe operations can be enhanced by correct design of device-level control algorithms, and protocols, procedures and operator training at the control-room level, but all can fail. Moreover, these elements exchange data and issue commands via vulnerable communication layers. In order to secure these gaps and enhance operational safety, we believe monitoring of command sequences must be combined with an awareness of physical device limitations and automata models that capture safety mechanisms. One way of doing this is by leveraging specification-based intrusion detection to monitor for physical constraint violations. The method can also verify that physical infrastructure state is consistent with monitoring information and control commands exchanged between field devices and control centers. This additional security layer enhances protection from both outsider attacks and insider mistakes. We implemented specification-based SCADA command analyzers using physical constraint algorithms directly in the Bro framework and Broccoli APIs for three separate scenarios: a water heater, an automated distribution system, and an over-current protection scheme. To accomplish this, we added low-level analyzers capable of examining control system-specific protocol packets for both Modbus TCP and DNP3, and also higher-level analyzers able to interpret device command and data streams within the context of each device's physical capabilities and present operational state. Thus the software that we are making available includes the Bro/Broccoli scripts for these three scenarios, as well as simulators, written in C, of those scenarios that generate sample traffic that is monitored by the Bro/Broccoli scripts. In addition, we have also implemented systems to directly pull cyber-physical information from the OSIsoft PI historian system. We have included the Python scripts used to perform that monitoring.

Source record↗

DOE OSTI2013

Resilience Measurement Index: An Indicator of Critical Infrastructure Resilience

The world faces numerous threats from both natural and man-made sources. Since the beginning of the 21 st century, in the United States alone, we have experienced several devastating events. Incidents such as the attacks on the World Trade Center in 2001, the Northeast blackout in 2003, Hurricane Katrina in 2005, and Superstorm Sandy in 2012 have had far-reaching impacts that have directly affected our society’s well-being. Although current efforts that have focused on preventing or mitigating the impact of incidents have achieved admirable results, a more comprehensive approach is needed to improve the nation’s overall resilience. An all-hazards methodology that emphasizes not only protection but also preparedness, mitigation, response, and recovery programs and capabilities is desired. Presidential Policy Directive 21 defines 16 critical infrastructure sectors that are essential to the nation’s security, public health and safety, economic vitality, and general quality of life (White House, 2013). If the operations of these critical infrastructure sectors are essential, their protection and resilience is paramount. As stated by President Obama, “Our goal is to ensure a more resilient Nation—one in which individuals, communities, and our economy can adapt to changing conditions as well as withstand and rapidly recover from disruption due to emergencies” (Department of Homeland Security, 2010a). Enhancing the resilience of critical infrastructure requires its owners/operators to determine the ability of the system to withstand specific threats, minimize or mitigate potential impacts, and to return to normal operations if degradation occurs. Thus, a resilience methodology requires the comprehensive assessment of critical infrastructure systems/assets—from threat to consequence. The methodology needs to support decision-making for risk management, disaster response, and business continuity. Considering these issues, the Infrastructure Assurance Center at Argonne National Laboratory, in partnership with the Protective Security Coordination Division of the U.S. Department of Homeland Security (DHS), has developed an index, the Resilience Measurement Index (RMI), to characterize the resilience of critical infrastructure.

Petit, F. D. P.↗

DOE OSTI2014

HC-NIDS: signatures and simulations for detecting cyber-attacks aiming to cause damage against cyber-physical energy systems

Source record↗

DOE OSTI2023

Effect of surface oxides on tritium entrance and permeation in FeCrAl alloys for nuclear fuel cladding: a review

Abstract Iron-chromium-aluminum (FeCrAl) alloys are being considered for the cladding of uranium dioxide fuel in light water reactors (LWRs). FeCrAl alloys have good mechanical properties at temperatures of 300 °C and higher, and have superlative resistance to attack by steam at temperatures of up to 1000 °C and higher. A concern has been raised that the use of FeCrAl for cladding would result in a higher content of tritium in the reactor coolant as compared with the current system where the cladding is a zirconium based alloy. This review shows that the flux of tritium from the fuel rod cavities to the coolant across the fuel cladding wall will be greatly reduced by the presence of oxides on the surface of the cladding. The review of current literature and permeation data show that (a) protective oxides are expected to be present on both sides of the FeCrAl cladding, and (b) depending on the characteristics of these oxide layers it is reasonable to expect about two–three orders of magnitude reduction in tritium permeation, relative to the permeation response in clean, unoxidized condition for FeCrAl steels of interest, around 277 °C–377 °C temperatures.

Electrochemistry↗

DOE OSTI2024

Tritium Extraction from FLiBe using a Permeation Against Vacuum (PAV): Impact of Surface Potentials, Currents, and Coupling PAV to Sacrificial Anodes

Savannah River National Laboratory (SRNL) is exploring a concept of pairing a LiF-BeF2 (FLiBe) immersed Permeation Against Vacuum (PAV) tritium extraction system with a sacrificial anode. Several fusion concepts utilize FLiBe for tritium breeding, and breeding of tritium would occur from neutron interactions with the Li component, creating corrosive TF and/or T2. In absence of a redox buffered system, the TF would be able to attack containment materials until neutralized. One way to neutralize TF is to contact it with an active metal such as Be or Li which would preferentially combine with the fluorine in the TF to form BeF2 or LiF, respectively, and resulting in T2. When the active metal (e.g., Be) is oxidized, it will provide electrons, when T in TF is reduced and forms T2, it needs electrons. SRNL proposes to electrically link these two reactions and with the PAV to help drive the reactions faster than on their own and potentially increase T2 dissociation. In a soluble redox salt buffered system, it is expected that with sufficient buffering, T2, may form more rapidly and the core components would be more protected, but the soluble redox salt buffer would need to be occasionally regenerated, which could be accomplished by again contacting the salt with an active metal such as Be or Li, although in this case the cathodic reaction would be electrons coming from the shift in oxidative state of the redox buffer. The exploration of potential and current effects on the PAV and impacts of redox agents will be discussed.

Olson, Luke C.↗

DOE OSTI2018

Effects of Varying Composition and Kinetics on the Microstructural and Mechanical Properties of Polysiloxane Foams

Polysiloxane elastomers are used in a wide variety of applications including medicine, aerospace, and defense industries. Though these materials demonstrate many useful properties such as flexibility, resistance to chemical attack, electrical insulation, and biocompatibility, the mechanical properties and product integrity are sensitive and may degrade in harsh environments. Understanding the degradation mechanisms and their effects on the mechanical properties of foamed polysiloxanes has been the subject of many studies; however, current formulations still produce foams with poor mechanical and aging properties. The chemical complexity, environmental sensitivity, and multitude of synthesis and degradation reactions that continuously occur complicate predicting the physical and mechanical properties or aging behavior. These factors warrant continued investigations on the chemistry, microstructural characterizations, and aging behavior of these materials

36 MATERIALS SCIENCE↗

DOE OSTI2022

An Intelligent Distributed Ledger Construction Algorithm for IoT

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed a machine-learning approach with a multi-arm bandit that resolved these issues and was designed for auditing on limited devices. This algorithm was tested in a reinforcement-learning environment simulating the IOTA ledger's construction with a decision tree. This study showed through regret analysis and experimentation that this approach was secure against impulse manipulation attacks while remaining energy-efficient. Although the IOTA protocol was a pioneer for lightweight distributed ledgers, it is expected that future blockchain protocols will adopt techniques similar to those presented in this work.

multi-arm bandit↗

DOE OSTI2023

Gap Analysis of Supply Chain Cybersecurity for Distributed Energy Resources

A supply chain is the combination of the ecosystem of resources needed to design, manufacture, and distribute a product. In the context of supply chain cybersecurity, the resources that directly influence this ecosystem include software, data, and/or other digital components. Compromised equipment or software in the supply chain may lead to attacks such as financial loss; denial of service; a breach of confidential or proprietary information from a company, its customers, or its suppliers; ransomware that denies operation of automated equipment for payment; and malicious control actions that could damage equipment and endanger personnel. Currently 60.8% of US energy comes from fossil fuels, 18.9% comes from nuclear energy, and the last 20.1% comes from renewable sources. Federal Energy Regulatory Commission order FERC 2222 and Executive Order 14017 on America's Supply Chains are important milestones for safely expanding generation from renewable energy and achieving the goal of a decarbonized U.S. energy sector by 2035. This report analyzes gaps and opportunities in the supply chain currently available to the renewable energy sector, to help stakeholders formulate a coordinated response.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Feasibility of Applying a Human Bio-signals Monitoring to Minimize Insider Threats

With the on-going global war on terror, a potential terrorist attack on a Nuclear Power Plant (NPP) is getting a lot of attention. In particular, the potential threat of an insider is a major concern as it could lead to the loss of a nationally critical asset and thus deserves serious consideration. The current approach to preventing an insider threat is the Insider Mitigation Program (IMP) based on periodic self-assessment or peer and manager review of specific employees. These are potentially biased and subjective assessments and are unreliable. Also, as the approach is reactive-based, identifying a problem employee could be too late to protect NPP assets (i.e., confidential information and nuclear materials). Thus, a new approach for detecting and predicting an insider is necessary. We propose a proactive approach based on using bio-signals as an alternative. To address the vulnerability of current insider detection systems, our studies investigated the possibility of insider detection and prediction by using biosignals (electroencephalogram (EEG), electrocardiogram (ECG), and galvanic skin response (GSR)). But one main question remained in the previous studies was: Is the method using key EEG indicators specific enough to discern the difference between a normal worker's motivation level change and being ready to commit a crime? This study examined the answer to the question.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Towards a CAN IDS Based on a Neural Network Data Field Predictor

Modern vehicles contain a few controller area networks (CANs), which allow scores of on-board electronic control units (ECUs) to communicate messages critical to vehicle functions and driver safety. CAN provides a lightweight and reliable broadcast protocol but is bereft of security features. As evidenced by many recent research works, CAN exploits are possible both remotely and with direct access, fueling a growing CAN intrusion detection system (IDS) body of research. A challenge for pioneering vehicle-agnostic IDSs is that passenger vehicles' CAN message encodings are proprietary, defined and held secret by original equipment manufacturers (OEMs). Targeting detection of next-generation attacks, in which messages are sent from the expected ECU at the expected time but with malicious content, researchers are now seeking to leverage "CAN data models'', which predict future CAN messages and use prediction error to identify anomalous, hopefully malicious CAN messages. Yet, current works model CAN signals post-translation, i.e., after applying OEM-donated or reverse-engineered translations from raw data. We present initial IDS results testing deep neural networks used to predict CAN data at the bit level, targeting IDS capabilities that avoiding reverse engineering proprietary encodings. Our results suggest the method is promising for data with signals exhibiting dependence on previous or concurrent inputs.

Pawelec, Krzysztof↗

DOE OSTI2019

Polarized Radar for Detection and Automatic Non-Visual Assessment of Unmanned Aerial Systems

This Laboratory Directed Research and Development (LDRD) effort performed fundamental Research and Development (R&D) to develop a robust radar processing algorithm capable of assessing the difference between an Unmanned Aerial System (UAS) and a biological target such as a bird, based on mathematics applied to the polarized radar returns of the target object, alone. The current threats of using such a UAS as a delivery platform for a host of destructive components is a major concern for the protection of various assets. Most recently, on 14th Sept. 2019, dozens of suicide or kamikaze drones (UAV-X) coordinated an attack on two Saudi oil facilities that demonstrated the potential to disrupt global oil supplies. While radar-based UAS detection systems can detect UAS at ranges greater than 1-km, the issues of excessive Nuisance/False Alarm Rates (NAR/FAR) from natural sources (birds in particular) has not been sufficiently addressed. In this effort we describe and utilize the Adaptive Polarization Difference Imaging-based (APDI) algorithms for the detection and automatic non-visual assessment of Unmanned Aerial System applications. Originally developed for optical imaging and sensing of polarization information in nature, the algorithms developed here are modified to serve for the target detection purposes in counter-UAS (cUAS) environments. We exploit the polarization statistics of the observing scene for detection and identification of changes within the scene and assess from these changes for UAS/bird classifications. Several cases are considered from independent data sources, including numerically generated data, anechoic chamber data as well as experimental radar data, to show the applicability of the techniques developed here. The methods developed in this effort are designed to be used in cUAS setups but have shown promise for a multitude of other radar-based classification uses as well.

47 OTHER INSTRUMENTATION↗