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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Facility Cybersecurity Framework Best Practices

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought. The U.S. Department of Energy’s (DOE) Federal Energy Management Program (FEMP) funded the Pacific Northwest National Laboratory (PNNL) to develop various cybersecurity tools, trainings, and reports to aid federal facility managers – and other building owners and operators – in better applying frameworks and lessons learned from the National Institute of Standards and Technology (NIST) Cybersecurity Framework (CSF), risk management framework (RMF), DOE’s cybersecurity capability maturity model (C2M2), and a wide variety of industry best practices and guidance documents (i.e., NIST 800 series, Department of Defense United Facilities Criteria). This set of tools, collectively known as the FEMP Facility-Related Control System Cyber Toolkit (FRCS Cyber Toolkit)2, is focused on cybersecurity concerns from facility-related control systems and other operational technology (OT), such as industrial control systems (ICS). The FRCS Cyber Toolkit can be applied across six of the sixteen critical infrastructure sectors designated by the Department of Homeland Security, including government facilities, healthcare and public health, commercial facilities (e.g., public assembly, offices, lodging), financial services (e.g., banking and insurance), emergency services (e.g., fire and police stations), and information technology. With increasingly converged IT and OT systems, it is crucial to address OT cybersecurity considerations and assess how the seam of these two systems could impact the overall cybersecurity posture of a facility. The objective of this report is to provide an overview of the best possible method to use FRCS Cyber Toolkit (section 2.0) and distilled cybersecurity best practices for the federal facilities to address growing non-linear cyber threats (section 3.0). Recommendations in this document are aggregated from several NIST and other documents (see Appendix A for additional details).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Facility Cybersecurity Framework Best Practices Version 2.0

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Facility Cybersecurity Framework Best Practices Version 2.0

Federal facilities are increasingly adopting automation and connecting to the Internet creating an energy-internet-of-things environment that converges operational technology (OT) and information technology (IT). Today's buildings increasingly weave together networked sensors and cyber and physical systems that enable data to be collected, aggregated, exchanged, stored and monetized in new ways. Building technological advances have created new energy technology, services, markets and value creation opportunities (e.g. transactive energy, two-way grid communications, machine learning, and increased use of renewable and distributed energy resources). But as larger data sets are being exchanged at faster speeds between an increasing number of OT systems, it becomes more difficult to protect the security of the data lifecycle and the physical equipment it interacts with. These challenges are especially difficult to overcome because the economic and environmental gain (interoperability, big data, social networks and ubiquitous information sharing) are driving these prominent trends in the digital age. Often cybersecurity is an afterthought.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Towards the Quantum Internet: Entanglement Rate Analysis of High-Efficiency Electro-Optic Transducer

Coherent microwave-optical photon conversion is a key enabling technology for the Quantum Internet, since it allows entanglement distribution among superconducting-based network nodes. A high-efficiency electro-optic transducer based on three-dimensional superconducting radio-frequency (SRF) technology has recently been proposed at Fermilab. In this paper, we evaluate the impact of Fermilab's transduction hardware on the entanglement generation probability and the entanglement rate, which are two critical metrics from a communication engineering perspective. Furthermore, we provide some guidelines to increase the direct entanglement rate, i.e., the rate before any entanglement purification process. Our analysis shows that, through high-efficiency transduction, it is possible to reduce the network overhead. This preliminary work paves the way toward distantly interconnected superconducting quantum processors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Incremental Threshold Scheme Enabled IoT Group Key Management

Cyber landscape evolves rapidly. Internet of Things (IoT) and Edge Computing (EC) have rapidly become an integral part of the modern computing infrastructure. It is expected that there will be more than 50 billion active and connected IoT devices by 2025 [1]. Pervasive IoT/EC creates unprecedented opportunities bridging the gap between previously segregated cyber and physical spaces. However, this progress also brings along new security challenges. IoT devices typically have limited computation, communication, and storage resources. This leads to security architecture designs such as using symmetric keys for group communication. While secure and efficient in stable network settings, symmetric key solutions are ill-adapted for IoT's highly dynamic device mobility behavior and frequent group membership turnover. Whenever IoT members leave a group, the known symmetric keys cannot be made forgotten, posing a serious vulnerability. This leads to frequent re-groupings that require expensive re-authentication, key regeneration, and key redistribution in order to maintain IoT/EC security. We present a novel symmetric key management framework that integrate an Incremental Threshold Scheme (ITS) cryptographical function into communication protocol's key rotation mechanism to allow for secure and efficient symmetric key communication group member node revocation. This ITS-enabled key management framework alleviates the need of frequent and expensive re-grouping and re-keying needed by today's large and dynamic IoT/EC operations. We further applied this ITS-enabled key management framework to a distributed IoT/EC-integrated publish and subscribe framework for applicability validation.

Li, Mingyan↗
DOE OSTI2024

Unconventional Quantum Advantages for Computation (U-QuAC)

While quantum computing offers the promise of exponential advantages, limited quantum speedups are known, especially for practical applications. To open new avenues for quantum advantages, we propose Unconventional Quantum Advantages for Computation (U-QuACs), with respect to unconventional resources such as space (number of bits or quantum bits of memory required to solve a problem), accuracy of solution, communication, or energy consumption. We focus on space-efficient quantum algorithms, where we seek to design algorithms that solve a problem using much less space than the total size of the input. A natural setting in which space is critical is the streaming model of computation, where the input data arrives sequentially in pieces that must each be processed individually. Streaming is motivated by a variety of problems including analysis of internet traffic or social networks. We design the first exponential quantum space advantage for a natural streaming problem, which also constitutes the first quantum advantage for approximating a discrete optimization problem, albeit with respect to space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Secure LoRa Firmware Update with Adaptive Data Rate Techniques

Internet of Things (IoT) devices rely upon remote firmware updates to fix bugs, update embedded algorithms, and make security enhancements. Remote firmware updates are a significant burden to wireless IoT devices that operate using low-power wide-area network (LPWAN) technologies due to slow data rates. One LPWAN technology, Long Range (LoRa), has the ability to increase the data rate at the expense of range and noise immunity. The optimization of communications for maximum speed is known as adaptive data rate (ADR) techniques, which can be applied to accelerate the firmware update process for any LoRa-enabled IoT device. In this paper, we investigate ADR techniques in an application that provides remote monitoring of cattle using small, battery-powered devices that transmit data on cattle location and health using LoRa. In addition to issues related to firmware update speed, there are significant concerns regarding reliability and security when updating firmware on mobile, energy-constrained devices. A malicious actor could attempt to steal the firmware to gain access to embedded algorithms or enable faulty behavior by injecting their own code into the device. A firmware update could be subverted due to cattle moving out of the LPWAN range or the device battery not being sufficiently charged to complete the update process. To address these concerns, we propose a secure and reliable firmware update process using ADR techniques that is applicable to any mobile or energy-constrained LoRa device. The proposed system is simulated and then implemented to evaluate its performance and security properties.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Hybrid Quantum Networks with Discrete Polarizations and Continuous Quadrature Variables

Final Scientific/Technical Report for DOE Project DE-SC0022069. Quantum communication and computation systems have evolved along two largely independent paradigms: discrete-variable (DV) systems that encode information in qubits such as photon polarizations or photon-number states, and continuous-variable (CV) systems that encode information in optical field quadratures. Each approach offers distinct advantages—DVs provide low error rates and compatibility with single-photon platforms, while CVs support deterministic operations and efficient quantum state manipulation. A fundamental challenge for building a scalable Quantum Internet lies in interfacing these two regimes into a unified hybrid architecture that can coherently distribute and process quantum information across heterogeneous quantum nodes. This project aims to develop and demonstrate a hybrid optical quantum network that seamlessly integrates DV and CV systems. Specifically, we investigate a new class of hybrid entanglement between the discrete polarizations of single photons and the continuous quadrature variables of optical cat states, overcoming incompatibilities in existing DV–CV demonstrations. Using this new entanglement resource, the team investigates a multi-node hybrid quantum local area network (Q-LAN) testbed capable of DV–CV entanglement generation, swapping, and distribution across fiber links.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

5G Enabled Energy Innovation: Advanced Wireless Networks for Science

Digital wireless communication has become a foundational technology for the nation. The U.S. Department of Energy’s Office of Science (DOE-SC) is the Nation’s largest supporter of basic research in the physical sciences discovering new materials, designing advanced microelectronics, and understanding the physics of radio frequency signaling. The expanding national rollout of a new fifth-generation (5G) mobile network, coupled with the torrent of scientific data generated by next-generation devices such as battery-powered Internet of Things (IoT) sensors, has created an urgent need to enhance cutting-edge wireless technology. Breakthroughs in the deployment, integration, security, and operational range of wireless networking can provide new scientific capabilities for the next decade - from autonomous mobile instruments for scientific user facilities to intelligent sensors networks distributed over thousands of kilometers to study environmental processes. To realize this promise, however, we must continue to drive innovations in computing, artificial intelligence (AI), advanced materials, high-speed networking, and microelectronics. In March 2020, the DOE-SC convened a workshop to identify the potential opportunities and explore the scientific challenges of advanced wireless technologies.

42 ENGINEERING↗
DOE OSTI2025

EUREICA: Efficient UltRa Endpoint IoT-enabled Coordinated Architecture

The electricity grid has evolved from a physical system to a cyber-physical system with digital devices that perform measurement, control, communication, computation, and actuation. The increased penetration of distributed energy resources (DERs) that include renewable generation, flexible loads, and storage provides extraordinary opportunities for improvements in efficiency and sustainability. However, they can introduce new vulnerabilities in the form of cyberattacks, which can cause significant challenges in ensuring grid resilience. The purpose of this project was to develop a framework ((Efficient, Ultra-REsilient, IoT-Coordinated Assets, or EUREICA)for achieving grid resilience through suitably coordinated assets including a network of Internet of Things (IoT) devices, and a local electricity market (LEM) to identify trustable assets and carry out this coordination. Situational Awareness (SA) of locally available DERs with the ability to inject power or reduce consumption is enabled by the market, together with a monitoring procedure for their trustability and commitment. Experiments conducted during this project demonstrated that, with this SA, a variety of cyberattacks can be mitigated using local trustable resources without stressing the bulk grid. The demonstrations were carried out using a variety of high-fidelity co-simulation platforms, real-time hardware-in-the-loop validation, and a utility-friendly simulator.

14 SOLAR ENERGY↗
DOE OSTI2022

Quantum computing in power systems

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today's power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Precursor Analysis Report: SQL Slammer Worm Infection of Davis-Besse Nuclear Power Plant 2003

The SQL Slammer Worm Infection of Davis-Besse Nuclear Power Plant 2003 Precursor Analysis Report leverages publicly available information about Davis-Besse’s 2003 cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. On 25 January 2003, the SQL Slammer worm infected more than 90% of vulnerable hosts and crashed the internet in 10 to 15 minutes, making it one of the fastest spreading worms in history. SQL Slammer is a fileless, memory-resident worm that remotely exploits a stack-based buffer overflow vulnerability on local hosts to intensively scan and rapidly self-propagate across the internet. The worm infected approximately 300,000 unpatched hosts running Microsoft Structured Query Language (SQL) Server 2000 or Microsoft Desktop Engine (MSDE) 2000 with SQL Server Resolution Service. The SQL Slammer worm indirectly infected FirstEnergy’s Davis-Besse nuclear power plant by first infecting a consultant’s company network server and then propagating through an external misconfigured connection into Davis-Besse’s site network. The infection caused major network congestion, slow performance, data overloads, and the inability of local hosts to communicate with each other, which eventually caused a loss of availability and a loss of view when the Safety Parameter Display System (SPDS) and Plant Process Computer (PPC) crashed. At the time of the infection, the plant was already offline, the digital monitoring systems had redundant analog backups, and the plant control and safety functions were not affected, so there were no concerns of a safety breach. However, this incident resulted in many lessons learned and spawned important discussions about cybersecurity’s role in nuclear safety and electric power reliability regulation, policy, and guidance. Researchers and analysts identified 10 unique techniques utilized during the attack with a total of 640 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Eight of the identified techniques used during Davis-Besse cyber attack were precursors to the triggering event. Analysis identified 596 observables associated with these precursor techniques, 428 of which were assessed to have an increased likelihood of being perceived in the 331 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Blockchain-Based Man-in-the-Middle (MITM) Attack Detection for Photovoltaic Systems

Cybersecurity of photovoltaic (PV) systems entails a much larger scope than just encryption and firewall of communications. For instance, integrity of data in transit between inverters and a cloud server can be compromised by authorized third-party, devices, and internal network within security perimeter (i.e., man-in-the-middle (MITM) attack). To address this challenge, this paper proposes a blockchain-based MITM attack detection method for a PV system. A breakthrough method includes screening network data, network intrusion detection, and hash comparison of in-transit data using distributed ledgers. Furthermore, the proposed method is implemented in Internet-of-Thing (IoT) security modules as clients of a blockchain network and validated by experiments.

blockchain↗
DOE OSTI2023

A Privacy-Aware Federated Learning Framework for Distributed Energy Resource Analytics in Constrained Environments

To be resilient against extreme weather events, the rural communities in Puerto Rico are leveraging distributed energy resources (DER). However, computing frameworks sup-porting the grid in critical decision-making are still largely centralized. Sensitive consumer data are transmitted over the Internet or cellular networks to a secondary or tertiary node. It guarantees better situational awareness at the cost of a wider attack surface, jeopardizing user privacy, as more DER come online. Cloud, Edge, and Fog computing all require data aggregation at some level. This paper introduces a privacy-aware federated learning framework that leverages the Fog model by pushing analytics all the way to the DER and load assets. These local models train on individual asset data and transmit only learned parameters (such as weights) over secure communications to a global decision-maker. By abstracting personally identifiable consumer data without impacting decision optimality, this framework better aligns with distributed power generation paradigm.

Sundararajan, Aditya↗
DOE OSTI2021

Enabling Interoperable SCADA Communications for PV Inverters through Embedded Controllers

The percentage integration of photovoltaic (PV) inverters in the field has increased significantly in the past 5 years. Regardless of the size of the PV plants and the inverters (residential vs. commercial), it is becoming crucial that these devices have the capability to communicate with peers (other smart devices) and with components that are at a hierarchy above the inverters (e.g., supervisory control and data acquisition (SCADA) systems, distributed controllers, and data managers). This project aims to develop a standard SCADA software code for inverters’ embedded controllers that will enable interoperability with other components in the system. To achieve this, the code will be developed using two different protocols: Distributed Network Protocol 3 and International Electrotechnical Commission 61850. The developed code is aimed to be deployed in simple embedded controllers. It will be tested in the National Renewable Energy Laboratory’s (NREL’s) Energy Systems Integration Facility. The tested code will then be made available through Triangle MicroWorks’s (TMW’s) software platform. The primary objectives of this project include training the NREL team with TMW’s embedded controller libraries, developing an interoperable communication code for embedded controllers, successfully testing and deploying the code, and demonstrating the newly developed code in a conference.

14 SOLAR ENERGY↗
DOE OSTI2022

Lessons Learned on the Interface Between Quantum and Conventional Networking

The future Quantum Internet is expected to be based on a hybrid architecture with core quantum transport capabilities complemented by conventional networking. Practical and foundational considerations indicate the need for conventional control and data planes that (i) utilize extensive existing telecommunications fiber infrastructure, and (ii) provide parallel conventional data channels needed for quantum networking protocols. We propose a quantum-conventional network (QCN) harness to implement a new architecture to meet these requirements. The QCN control plane carries the control and management traffic, whereas its data plane handles the conventional and quantum data communications. We established a local area QCN connecting three quantum laboratories over dedicated fiber and conventional network connections. We describe considerations and tradeoffs for layering QCN functionalities, informed by our recent quantum entanglement distribution experiments conducted over this network.

Alshowkan, Muneer↗
DOE OSTI2021

A Commercial Building Plug Load Management System that Uses Internet of Things Technology to Automatically Identify Plugged-In Devices and Their Locations

Plug and process loads (PPLs) account for a large portion of U.S. commercial building energy use. There is a huge potential to reduce whole building consumption by targeting PPLs for energy savings measures or implementing some form of plug load management (PLM). Despite this potential, there has yet to be a widely adopted commercial PLM technology. This paper describes the Automatic Type and Location Identification System (ATLIS), a PLM system framework with automatic and dynamic load detection (ADLD). ADLD gives PLM systems the ability to automatically identify devices as they are plugged into the outlets of a building. The ATLIS framework takes advantage of smart, connected devices to identify device locations in a building, meter and control their power, and communicate this information to a central database. ATLIS includes five primary capabilities: location identification, communication, control, energy metering, and data storage. A laboratory proof of concept (PoC) demonstrated all but the energy metering capability, and these capabilities were validated using a series of system tests. The PoC was able to identify when a device was plugged into an outlet and the location of the device in the building. When a device was moved, the PoC's dashboard and database were automatically updated with the new location. The PoC implemented controls to devices from the system dashboard so that devices maintained correct schedules regardless of where they were plugged in within the building. ATLIS's primary technology application is improved PLM, but other applications include asset management, energy audits, and interoperability for grid-interactive efficient buildings. An ATLIS-based system could also be used to direct power to critical devices, such as ventilators, during a brownout or blackout. Such a framework is an opportunity to make PLM more widespread and reduce the amount of energy consumed by PPLs in current and future commercial buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Measurement and applications: Exploring the challenges and opportunities of hierarchical federated learning in sensor applications

Sensor applications have become ubiquitous in modern society as the digital age continues to advance. AI-based techniques (e.g., machine learning) are effective at extracting actionable information from large amounts of data. An example would be an automated water irrigation system that uses AI-based techniques on soil quality data to decide how to best distribute water. However, these AI-based techniques are costly in terms of hardware resources, and Internet-of-Things (IoT) sensors are resource-constrained with respect to processing power, energy, and storage capacity. These limitations can compromise the security, performance, and reliability of sensor-driven applications. To address these concerns, cloud computing services can be used by sensor applications for data storage and processing. Unfortunately, cloud-based sensor applications that require real-time processing, such as medical applications (e.g., fall detection and stroke prediction), are vulnerable to issues such as network latency due to the sparse and unreliable networks between the sensor nodes and the cloud server [1]. As users approach the edge of the communications network, latency issues become more severe and frequent. A promising alternative is edge computing, which provides cloud-like capabilities at the edge of the network by pushing storage and processing capabilities from centralized nodes to edge devices that are closer to where the data are gathered, resulting in reduced network delays [2], [3].

Po-Leen Ooi, Melanie↗