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Maturity models can be used to provide government agencies, industry associations, and organizations operating nuclear facilities with the ability to quickly evaluate the maturity of their cybersecurity programs and identify areas to prioritize for improvement. The Cybersecurity Capability Maturity Model (C2M2) was developed by the U.S. Department of Energy to allow organizations in the energy sector to evaluate the programmatic capabilities of their cybersecurity programs in a consistent manner, communicate programmatic maturity information, prioritize cybersecurity investments in targeted areas of concern, and track how the maturity of their cybersecurity program evolves over time. The C2M2 is designed for use by any critical infrastructure organization regardless of ownership, structure, or size. The C2M2 can be easily fine-tuned to access the maturity of nuclear cybersecurity programs and their application at individual facilities. Built on a foundation of existing cybersecurity standards, frameworks, programs, and initiatives, the model features 10 security domains. Performance in each security domain is characterized using a structured set of cybersecurity practices that represent activities an organization can perform to improve cybersecurity in their domain. Each practice can be quickly evaluated as being either fully, largely, partially, or not implemented. Once practices are evaluated for each security domain, the model defines four maturity indicator levels that apply independently to each domain in the model. To earn a maturity level in a given domain, an organization must adequately perform all the practices for that maturity level and its predecessor level(s). A small assessment team can conduct a C2M2 assessment in a single day. A screening version of the C2M2 allows an initial look at the maturity of nuclear cybersecurity programs that could be completed in under an hour.
A review of geothermal sector-specific cybersecurity vulnerabilities and risks (consequences) was conducted at the request of the Geothermal Technologies Office (GTO). The vulnerabilities and risks reviewed in this study have relevance to achieving the 2019 GeoVision Report (DOE GTO 2019) technological advancements and expected sector growth. The study offers areas for consideration but does not quantify the likelihood (frequency) of the consequences. This cybersecurity analysis project represents a proactive effort to identify areas to enhance cybersecurity in geothermal development and operations. It was not initiated to address any immediate threat or specific known risk. Of the eight identified vulnerabilities analyzed, the review identified reservoir data system monitoring as one that is unique to geothermal systems and may warrant further investigation to better understand risk and mitigation. A detailed analysis of the other vulnerabilities may highlight additional uniqueness relative to other industries. Further research actions are recommended to better quantify risk and enhance cybersecurity preparedness of the sector. As the geothermal industry grows, the cybersecurity strategies to be deployed will be of increasing importance to ensure resilient, reliable, and secure clean energy for years to come.
Software Defined Networking for Operational Technologies, referred to as OT-SDN, is a leading technology to secure critical infrastructure and command and control (C2) systems. As the name implies, OT-SDN networks are programmable, which allows system owners to utilize the characteristics of their physical process to inform the security of their network. There are best practices for deploying OT-SDN into an environment, whether it is all at once or over time (hybrid) that the network is converted to SDN technologies. Through the development of data mining tools and standardized process control, OT-SDN can be deployed reliably. These tools will minimize or eliminate any communication failures during the transition and provide the network owner with complete documentation of their environment. This documentation could enable or facilitate the network owner to pass any audits or policy checks (Authority to Operate) before being allowed to utilize the OT-SDN infrastructure.
Graphics Processing Units (GPUs) are ubiquitous components used across the range of today’s computing plat- forms, from phones and tablets, through personal computers, to high-end server class platforms. With the increasing importance of graphics and video workloads, recent processors are shipped with GPU devices that are integrated on the same chip. Integrated GPUs share some resources with the CPU and as a result, there is a potential for microarchitectural attacks from the GPU to the CPU or vice versa. We consider the potential for covert channel attacks that arise either from shared microarchitectural components (such as caches) or through shared contention domains (e.g., shared buses). We illustrate these two types of channels by developing two reliable covert channel attacks. The first covert channel uses the shared LLC cache in Intel’s integrated GPU architectures. The second is a contention based channel targeting the ring bus connecting the CPU and GPU to the LLC. This is the first demonstrated microarchitectural attack crossing the component boundary (GPU to CPU or vice versa). Cross-component channels introduce a number of new challenges that we had to overcome since they occur across heterogeneous components that use different computation models and are interconnected using asymmetric memory hierarchies. We also exploit GPU parallelism to increase the bandwidth of the communication, even without relying on a common clock. The LLC based channel achieves a bandwidth of 120 kbps with a low error rate of 2%, while the contention based channel delivers up to 400 kbps with a 0.8% error rate. We also demonstrate a proof- of-concept prime-and-probe side channel attack that probes the full LLC from the GPU.
The National Renewable Energy Laboratory (NREL) offers unique research capabilities to help innovators and partners prepare for an energy future with increased connectivity, diversity, and uncertainty.
Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks pose a serious threat to computing networks - especially to critical systems within the U.S. electrical grid. As attack mechanisms have increased in complexity and variety, more sophisticated detection mechanisms have become necessary to ensure network security. This paper explores the use of artificial intelligence to automate the process of detection and mitigation of DoS and DDoS attacks within the framework of Software-Defined Networking (SDN), to a high degree. Machine learning algorithms are trained to recognize DoS and DDoS attacks and are deployed in real-time to mitigate malicious network traffic. The results show a well-tuned gradient-boosted decision tree detecting DoS and DDoS attacks, as well as initial successful mitigation of attacks within an SDN framework.
Semiconductor manufacturing is a highly complex. Fabrication plants must deal with re-entrant flows to support multiple types of wafers being produced simultaneously, each with their own deadlines and specifications. The manufacturing process itself depends upon the ability to control and programmatically adjust a variety of environmental conditions including temperature, humidity, and air quality. In addition, wafer fabrication consumes large amounts of electricity. Emerging technologies may help reduce the energy footprint of such facilities but can introduce cybersecurity risks. Therefore, this paper presents a modeling and simulation framework to quantify tradeoffs between operational measures of performance, energy consumption, and cybersecurity controls. We augment the Intel Minifab model, with the Purdue Enterprise Reference Architecture (PERA) for cybersecurity as well as tool-level energy consumption data from a real-world semiconductor manufacturing testbed. In this manner, we intend to provide stakeholders with a systematic, data-driven approach to evaluate emerging risks within the manufacturing process.
Overview of Idaho National Laboratory Cybersecurity Support to the Department of Homeland Security.
As part of the Securing Solar for the Grid (S2G): Cybersecurity for Solar Systems workshop at RE + in Las Vegas, Nevada, NREL researchers discuss an ongoing effort to develop cybersecurity guidance for vendors and operators of distributed energy resource management systems (DERMS). This guide will prioritize cybersecurity best practices that can be testing and developed for a potential future standard. This presentation will highlight NREL's ongoing work in this area and future areas of research.
NREL's advanced distribution management system (ADMS) research helps utilities meet customer expectations of reliability, power quality, renewable energy use, data security, and resilience to natural disasters and other threats.
Function-based taxonomies are relational mapping tools used to clearly illustrate how an organization delivers Critical Functions by using various people, processes, technologies, information, and infrastructure (PPTII). Critical Functions are the actions or activities that make up the organization’s primary purpose. Enabling Functions are the combination of PPTII used by the organization to deliver their Critical Functions. A function-based taxonomy provides a framework to categorize information and related artifacts that document an organization’s unique implementation of PPTII for Critical Function delivery. The ideal state of a function-based taxonomy is to organize the existing knowledge the organization already has throughout their numerous systems, policies, people, procedures, and configurations. A well-organized taxonomy helps organizations to effectively leverage their knowledge by clearly identifying dependencies and connections. This document is the result of combined engineering and analytical experience and describes a repeatable method for producing function-based taxonomies.
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A program that defines and assesses the dynamic risk of software vulnerabilities and considers the dynamic risks into patch scheduling to reduce security risks posed by vulnerabilities and provide formal guidance to security operations at various organizations.
As the pace of renewable energy development increases, so does the challenge and opportunity to develop innovative solutions to secure renewable technologies. Four national laboratories National Renewable Energy Laboratory, Sandia National Laboratories, Pacific Northwest National Laboratory, and Idaho National Laboratory are working together to increase cybersecurity maturity levels for solar stakeholders. INL will discuss a DER threat briefing and operator tools and training developed under the Securing Solar for the Grid (S2G) project.
Microreactors and small modular reactors (SMRs) are anticipated to be key elements in the United States' carbon-free energy portfolio, serving as reliable power sources for remote communities, disaster relief zones, extraterrestrial deployments, and backup power needs. Microreactors employ technologies that are substantially more advanced and recent compared to conventional reactors. Furthermore, they are of a drastically smaller scale and are designed to be operated in a diverse set of locations, offering operational flexibility and mobility. In addition, the autonomous or semi-autonomous operation of microreactors with minimal or no on-site staff is anticipated. These factors give rise to specific challenges with regards to their safety and security. The present work investigates considerations related to heat pipe operation, reactor transport, and cyber/cyberphysical security to ensure the indirect and direct consequences of nefarious actors’ actions are understood and can be mitigated by design or through physical security measures. In addition, future directions are proposed for consideration by both HPMR designers and for regulators.
A disruption in CrowdStrike’s Falcon cybersecurity platform on July 19th, 2024, caused worldwide chaos. This event highlights the imperative need for cloud security measures for networks that are critically reliant on cloud technology. This incident negatively impacted air travel, government networks, and critical infrastructure sectors such as hospitals and financial institutions. While no electric utilities had a physical impact, and few had an IT impact, there were issues created by loss of cloud services, and other interrelated industries. For utilities and energy distribution organizations, understanding and mitigating these risks is essential. The Cirrus tool offers a strategic solution engineered to weave cloud integration seamlessly into the fabric of operational management, thereby enhancing resilience and streamlining efficiency in the face of digital challenges.