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At least 145 records · Page 8

Architecture and Methods for Substation SCADA Cybersecurity: Best Practices

There are over 3000 electricity providers in the United States, encompassing investor and publicly owned utilities as well as electric cooperatives. There has been ongoing trends to increasingly automate and provide remote control and monitoring of electric energy delivery systems. The deployment of computer network technologies has increased the efficiency and reliability of electric power infrastructure. However, the increased use of digital communications has also increased the vulnerability to malicious cyber attacks [1]. In 2004 the National Research Councils (National Academies) formed a committee of specialists to address these vulnerabilities and propose possible solutions with an objective to prioritize the R&D needs for developing countermeasures. The committee addressed many potential concerns in the electric power delivery system and classified them based upon different criteria and presented recommendations to minimize the gap between the academic research directions and the needs of the electric utility industry. The complexity and diversity of the electric power delivery system in the U.S. has opened many ports for attackers and intruders [1]. This complexity and diversity is attributed to the fact that power delivery system is a network of substations, transmission and distribution lines, sub-networks of controlling, sensing and monitoring units, and human operator involvement for running the system [1]. Accordingly, any incident such as the occurrence of a fault or disturbance in this complex network cannot be deferred and should be resolved within an order of milliseconds, otherwise there is risk of large-scale outages similar to the occurrences in India and the U.S. in 2003 [2]. There are three main vulnerabilities in supervisory control and data acquisition (SCADA) systems commonly identified—physical vulnerability, cyber vulnerability and personal vulnerability [1]. In terms of cyber threats, SCADA systems are the most critical elements in the electric power grid in the U.S. Unauthorized access to a SCADA system could enable/disable unexpected equipment (such as disable the protection system or a circuit breaker) which could cause large scale disruptions of electric power delivery. This paper provides an overview of power system SCADA technologies in transmission substations (Section 2) and summarizes the best practices for implementing a cyber security program. After introducing SCADA system operations in Section 2, a description of the security challenges for SCADA systems is presented in Section 3. In Section 4, NECRC Critical Infrastructure Protection standards CIP-002 through CIP-009 are summarized. An overview of industry best practices is presented in Section 5.

97 MATHEMATICS AND COMPUTING↗

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

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

24 POWER TRANSMISSION AND DISTRIBUTION↗

Software Framework for Federated Science Instruments

There is an unprecedented promise of enhanced capabilities for federations of leadership computing systems and experimental science facilities by leveraging software technologies for fast and efficient operations. These federations seek to unify different science instruments, both computing and experimental, to effectively support science users and operators to execute complex workflows. The FedScI project addresses the software challenges associated with the formation and operation of federated environments by leveraging recent advances in containerization of software and softwarization of hardware. We propose a software framework to streamline the federation usage by science users and it’s provisioning and operations by facility providers. A distinguishing element of our work is the support for improved interaction between experimental devices, such as beam-line instruments, and more traditional high-performance computing resources, including compute, network, storage systems. We present guiding principles for the software framework and highlight portions of a current prototype implementation. We describe our science use case involving neutron imaging beam-lines (SNAP/BL-3, Imaging/CG-1D) at the Spallation Neutron Source and High Flux Isotope Reactor facilities at Oak Ridge National Laboratory. Additionally, we detail plans for a more direct instrument interaction within a federated environment, which could enable more advanced workflows with feedback loops to shorten the time to science.

Naughton III, Thomas↗

The CLAS12 Data Acquisition System

The CLAS12 Data Acquisition System was designed and built as part of the CLAS12 detector project in Hall B at Jefferson Laboratory. This article contains a full description of the system, including requirements, design, hardware, and software descriptions, as well as the achieved performance. The associated computing, network, and slow controls systems are also described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Boost of the Bio-memristor Performance for Artificial Electronic Synapses by Surface Reconstruction

Biomaterial-based memristors (bio-memristors) are often adopted to emulate biological synapse functions and applied to construct neural computing networks in brain-inspired chip systems. However, the randomness of conductive filament formation in bio-memristors inhibits their switching performance by causing the dispersion of the device-switching parameters. In this case, a facile porous silk fibroin (p-SF) memristor was obtained through a protein surface reconstruction strategy, in which the size of the hole can be adjusted by the density of hybrid nanoseeds. Here, the porous SF memristors exhibit greatly enhanced electrical characteristics, including uniform I-V cycles, centralized distribution of the switching voltages, and both high and low resistances, compared to devices without pores. The results of three-dimensional (3D) simulations based on classical density functional theory (cDFT) suggest that the reconstructed pores in the SF layers guide the formation and fracture of Ag filaments under an electric field and enhance the overall conductivity by separating Ag + ion and electron diffusion pathways. Ag + ions are predicted to preferentially diffuse through pores, whereas electrons diffuse through the SF network. Interestingly, the device conductance can be bidirectionally modulated gradually by positive and negative voltages, can faithfully simulate short-term and long-term plasticity, and can even realize the triplet-spike-timing-dependent plasticity (triplet-STDP) rule, which can be used for pattern recognition in biological systems. The simulation results reveal that a memristor network of this type has an accuracy of ~95.78% in memory learning and the capability of pattern learning. This work provides a facile technology route to improve the performance of bionic-material memristors.

36 MATERIALS SCIENCE↗

Artificial intelligence-based predictive modeling for imaging neutral particle analyzers on the DIII-D tokamak

The Imaging Neutral Particle Analyzer (INPA) at DIII-D is a diagnostic system used to accurately resolve the energy and spatial distributions of fast ions in fusion plasmas. A novel artificial intelligence (AI) technique named INPA-net is based on Reservoir Computing Networks and developed here to predict active and passive signals produced by charge-exchange reactions from injected and edge-cold neutrals, respectively, in magnetically confined fusion plasmas. This model is trained using a set of 21 time domain signals between 0 s to 3.35 s that includes injected beam and thermal plasma information, and 6444 real 2D experimental images of the INPA in 12 plasma discharges at DIII-D. The trained neural network is able to forecast experimental images in real-time. The model achieves an R-squared value of 0.91, which is higher than the 0.83 value achieved by a simple linear regression model. This improvement highlights the model's enhanced predictive accuracy for measured images from the validation set. This AI approach is valuable due to its rapid response times and potential for integration into real-time plasma control systems. A version of this model capable of generating syntehic images would be useful for the real-time monitoring of fast-ion transport. A comprehensive sensitivity study reveals that INPA-net maintains high performance even with variations in the input parameters, indicating the model's robustness and reliability. While developed for the INPA, the underlying architecture is adaptable and may be applied to various 2D imaging diagnostics in fusion research.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Nonreciprocal Dissipation Engineering via Strong Coupling with a Continuum of Modes

Optical nonreciprocity plays a key role in almost every optical system, directing light flow and protecting optical components from backscattered light. Controllable forms of on-chip nonreciprocity are needed for the robust operation of increasingly sophisticated photonic integrated circuits (PICs) in the context of classical and quantum computation, networking, communications, and sensing. However, it has been challenging to achieve wideband, low-loss optical nonreciprocity on-chip. In this paper, we demonstrate strong coupling and Rabi-like energy exchange between photonic bands, possessing a continuum of modes, to unlock nonreciprocity and frequency translation over wide optical bandwidths in silicon. Using a traveling-wave phonon field to drive indirect interband photonic transitions, we demonstrate band hybridization that enables an intriguing form of nonreciprocal dissipation engineering. Using the converted mode to create a nonreciprocal dissipation channel, we demonstrate a frequency-neutral, low-loss (less than 1 dB) isolator with high nonreciprocal contrast (more than 14 dB) and broad operating bandwidth (more than 59 GHz). Additionally, through the implementation of complete interband conversion, we demonstrate a high extinction (more than 55 dB) optical frequency translation operation with near-unity efficiency.

Zhou, Yishu↗

Malicious Cyber Activity Detection using Zigzag Persistence

In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity, and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from various forms of malicious attacks, including network damage, data theft, and activity monitoring. We focus on the cybersecurity domain and investigate the detection of malicious activity using log data. We consider the dynamics of the log data and explore the changing topology of a hypergraph representation of this data to gain insights into the underlying activity. These hypergraphs capture complex interactions between processes, together with their temporal information. To study the changing topology we use zigzag persistence, which captures how topological features persist at multiple dimensions over time. We observe that this detects malicious activity in a cyber data set. To automate this detection we implement an autoencoder trained on a vectorization of the resulting zigzag persistence barcodes. Our experimental results demonstrate the effectiveness of the autoencoder in detecting malicious activity. Overall, this study highlights the potential of zigzag persistence and its combination with temporal hypergraphs for analyzing cybersecurity log data and detecting malicious behavior.

hypergraphs, temporal hypergraph, topological data↗

App2Net: Moving App Functions to Network & a Case Study on Low-latency Feedback

Recent advances in programmable networks enable custom processing of data at hundreds of gigabits per second. These advances can boost the performance of many distributed applications. Yet the high-level languages used by application developers are different from the data plane programming languages (such as P4 and NPL) used by network equipment. This language barrier slows innovation. Our hourglass-shaped architectural solution aims to lower this language barrier. This enables the application developer community to leverage programmable networks for achieving better performance. In this paper we propose a JSON-based intermediate representation to bridge the gap between applications and in-network computing. We demonstrate an instance of the solution in the context of a low-latency feedback application that enables SQL-based data filtering in a P4-based programmable environment. We also present a prototype compiler to convert an intermediate representation in JSON to P4 source.

Sankaran, Ganesh↗

An Energy Service Interface for Distributed Energy Resources

Renewable energy resources, particularly wind and solar photovoltaic, are becoming significant contributors to electric power generation. These re-sources will contribute towards achieving sustainable electric power systems. However, renewable resources will dramatically increase the demand for flexible power system operations. This paper proposes an energy service interface that will allow aggregated distributed energy resources, such as residential loads and inverter-based systems, to participate in NERC-defined smart energy reliability services. Such cyber-physical systems will increase system flexibility by ensuring match between energy supply and energy demand.Aggregation and coordinated dispatch of millions of distributed energy resources will require development of large-scale computing networks. Several smart grid interface-enabling technologies, including IEEE 2030.5, Common Smart Inverter Profile, SunSpec Modbus, and CTA 2045, are discussed. Residential loads are categorized by their static and dynamic energy characteristics to identify services in which they can participate. The business model for the energy services interface as well as probabilistic modeling for resource estimation are highlighted as future considerations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Quantifying the Spectrum of Denial-of-Service Attacks through Internet Backscatter

Denial of Service (DoS) attacks are a major threat currently observable in computer networks and especially the Internet. In such an attack a malicious party tries to either break a service, running on a server, or exhaust the capacity or bandwidth of the victim to hinder customers to effectively use the service. Recent reports show that the total number of Distributed Denial of Service (DDoS) attacks is steadily growing with "mega-attacks" peaking at hundreds of gigabit/s (Gbps). In this paper, we will provide a quantification of DDoS attacks in size and duration beyond these outliers reported in the media. We find that these mega attacks do exist, but the bulk of attacks is in practice only a fraction of these frequently reported values. We further show that it is feasible to collect meaningful backscatter traces using surprisingly small telescopes, thereby enabling a broader audience to perform attack intelligence research.

Blenn, Norbert↗

eZeeKonfigurator v1.0

eZeeKonfigurator is a web application and supporting tools for configuring Zeek (formerly Bro) systems. Zeek is an open-source tool developed at LBNL that's used to secure computer networks. A recent version of Zeek introduced the configuration framework, where changes can be made while the system is running. However, the provided method is difficult to operationalize, as it requires a set of text files to be deployed and updated across all the Zeek systems. eZeeKonfigurator provides an easy-to-use web interface to this. Users can view and modify options in a web application, and then those changes are deployed to the desired Zeek systems. Additionally, users benefit from additional features, such as: * Logging and auditing, to determine who made what change and when * Automated expiration of changes (e.g. an exception is added for 2 weeks, after which time it will be removed) * Validation of changes and verification that the change has been applied * Fine-grained role-based access

Grigorescu, Vlad↗

HOMER Economic Models - US Navy

This LETTER REPORT has been prepared by Idaho National Laboratory for US Navy NAVFAC EXWC to support in testing pre-commercial SIREN (Simulated Integration of Renewable Energy Networks) computer software models. In the logistics mode SIREN software simulates the combination of renewable power sources (solar arrays, wind turbines, and energy storage systems) in supplying an electrical demand. NAVFAC EXWC will create SIREN software logistics models of existing or planned renewable energy projects at five Navy locations (San Nicolas Island, AUTEC, New London, & China Lake), and INL will deliver additional HOMER computer models for comparative analysis. In the transient mode SIREN simulates the short time-scale variation of electrical parameters when a power outage or other destabilizing event occurs. In the HOMER model, a variety of inputs are entered such as location coordinates, Generators, PV arrays, Wind Turbines, Batteries, Converters, Grid costs/usage, Solar resources, Wind resources, Temperatures, Fuels, and Electric Loads. HOMER's optimization and sensitivity analysis algorithms then evaluate the economic and technical feasibility of these technology options and account for variations in technology costs, electric load, and energy resource availability. The Navy can then use HOMER’s optimization and sensitivity results to compare to those of the SIREN model. The U.S. Department of Energy (DOE) Idaho National Laboratory (INL) possesses unique expertise and experience in the software, hardware, and systems design for the integration of renewable energy into the electrical grid. NAVFAC EXWC will draw upon this expertise to complete mission requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

User Behavior Analytics

User Behaviour Analytics is the tracking, collecting and assessing of user data and activities. The goal is to detect misuse of user credentials by developing models for the normal behaviour of user credentials within a computer network and detect outliers with respect to their baseline.

99 GENERAL AND MISCELLANEOUS↗

Resilience: Concepts from Engineering, Ecology, and the Social Sciences

“Resilience” is fast becoming a key word for describing the desired result of the activities we group under the heading of “homeland security.” Department of Homeland Security (DHS) Secretary Napolitano has made resilience a key theme in her speeches, highlighting the efforts of DHS to “strengthen the resilience of ... infrastructure, computer networks, and of ... communities and citizens.” She has talked about resilience as “strengthening the ability for our systems, our cities, our towns, and our country to bounce back quickly from an attack or a natural disaster, and to be even stronger than before. This paper first provides an overview of resilience concepts from U.S. government and academic research sources. It then discusses resilience concepts and metrics from the academic literature in more detail, focusing on three types of resilience: engineering resilience, ecological resilience, and community and regional resilience. Next, it discusses system characteristics that have been associated with increased resilience. Based on this background, we propose a model of the infrastructure resilience analysis process. We then review LANL capabilities for each process element and indicate areas where capability development opportunities exist. Appendices provide additional information on funding sources and key players in infrastructure resilience, and a more detailed technical explanation of ecological resilience.

42 ENGINEERING↗

Final Report for Industrial Base Cybersecurity Initiative (IBCI) Project (FY2019)

Information security issues impact all manufacturing sectors and are particularly troublesome when designs for advanced weapons systems are lost via attacks that propagate through the relatively unprotected lower tiers of the nation's supply chains. The US Manufacturing Industrial Base (MIB) consists of suppliers and distributors that range in size from large prime contractors with extensive cybersecurity resources to small shops with little or no in-house information technology capabilities. The acquisition and maintenance of the technologies, systems, and financial resources needed to assure secure collaborations can be an overwhelming challenge for many manufacturers yet the cost of poor cybersecurity practices can lead to the compromise of national security information worth hundreds of millions of dollars. The Department of Defense Manufacturing Industrial Base Policy organization and the Department of Energy, Energy Efficiency and Renewable Energy Advanced Manufacturing Office have chartered the Los Alamos National Laboratory (LANL) and the Oak Ridge Y-12 National Security Complex (Y-12) to design, develop, and demonstrate a Manufacturing Threat Evaluation Wargaming System (MTEWS). The MTEWS concept is based on the use of a virtual model of the computer networks and cybersecurity protocols used across the MIB that will be continuously updated to reflect the dynamic threat environment. The MTEWS cyber-physical test range will demonstrate a prototype wargaming system that analyzes the impact of new and existing cybersecurity threats while also providing the information needed to sustain the integrity of the MIB supply chains. A long-term goal is the establishment of an enduring national manufacturing operations center that proactively responds to the continuously changing attacks that threaten the MIB and US national security. LANL and Y-12 have formed an Industrial Base Cybersecurity Initiative Team (IBCI), consisting of partners from the public, private and academic sectors, that is developing the MTEWS. To date, most of the project tasks have been centered on the technologies required to create a representative model of the MIB because this is a foundational element for the entire project. Modeling activities at the University of North Carolina at Charlotte (UNC Charlotte) have demonstrated a VMware-based prototype system that can accommodate a network model with up to 350 nodes and includes features such as the option to incorporate network scanning information when building the model and the ability to down select the elements of duplicative networks to a statistically significant subset that avoids redundantly duplicating network configurations. Broad Ordering Agreements have been established with UNC Charlotte and the University of West Florida (UWF) that support a variety of cybersecurity for manufacturing tasks and wide-spread endorsement has been received from government, industry and academia sectors concerning the IBCI goals and technical direction.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Models of TCP in high-BDP environments and their experimental validation

In recent years, the computer networking community has seen a steady growth in bandwidth-delay products (BDPs). Several TCP variants were created to combat the shortcomings of legacy TCP when it comes to operation in high-BDP environments. These variants, among which are CUBIC, STCP, and H-TCP, have been extensively studied in some empirical contexts, and some analytical models exist for CUBIC and STCP. However, since these studies have been conducted, BDPs have risen even more, and new bulk data transfer tools have emerged that utilize multiple parallel TCP streams. In view of these new developments, it is imperative to revisit the question: Which congestion control algorithms are best adapted to current networking environments? In order to help resolve this question, we contribute the following: (i) using first principles, we develop a general throughput-prediction framework that takes into account buffer sizes and maximum window constraints; (ii) we validate the models using measurements and achieve low prediction errors; (iii) we note differences in TCP dynamics between two experimental configurations and find one of them to be significantly more deterministic than the other; we also find that CUBIC and H-TCP outperform STCP, especially when multiple streams are used; and (iv) we present preliminary results for modelling multiple TCP streams for CUBIC and STCP.

Vardoyan, G.↗

SimCell Status Board

The Virtual SimCell is a method embodied in several software applications based on the Virtual Community Platform (VCP) (ANL-SF-11-049) and its Real-Time Dashboard (RTD) app. The purpose of this method is to more efficiently facilitate emergency preparedness exercises by allowing emergency preparedness exercise Simulation Cells -- SimCells -- to be established and managed through a computer network. SimCells take the place of organizations that would respond to actual emergencies, but are not participants in exercises of emergency preparedness plans. In effect, SimCells serve as actors portraying how those organizations would respond during real emergency events. The SimCell Status Board (SSB) is an RTD mini-app for controllers to communicate exercise events to players and each other by entering information into an integrated system of pre-defined data fields, displaying those data effectively, and preserving them for easy access during exercise evaluations.

Tanzman, Edward↗