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In the late 1980's, the traditional threat of anonymous break-ins to networked computers was joined by viruses and worms, multiplicative surrogates that carry out the bidding of their authors. Technologies for authentication and secrecy, supplemented by good management practices, are the principal countermeasures. Four articles on these subjects are presented.
The rise of grid modernization has been prompted by the escalating demand for power, the deteriorating state of infrastructure, and the growing concern regarding the reliability of electric utilities. The smart grid encompasses recent advancements in electronics, technology, telecommunications, and computer capabilities. Smart grid telecommunication frameworks provide bidirectional communication to facilitate grid operations. Software-defined networking (SDN) is a proposed approach for monitoring and regulating telecommunication networks, which allows for enhanced visibility, control, and security in smart grid systems. Nevertheless, the integration of telecommunications infrastructure exposes smart grid networks to potential cyberattacks. Unauthorized individuals may exploit unauthorized access to intercept communications, introduce fabricated data into system measurements, overwhelm communication channels with false data packets, or attack centralized controllers to disable network control. An ongoing, thorough examination of cyber attacks and protection strategies for smart grid networks is essential due to the ever-changing nature of these threats. Previous surveys on smart grid security lack modern methodologies and, to the best of our knowledge, most, if not all, focus on only one sort of attack or protection. This survey examines the most recent security techniques, simultaneous multi-pronged cyber attacks, and defense utilities in order to address the challenges of future SDN smart grid research. The objective is to identify future research requirements, describe the existing security challenges, and highlight emerging threats and their potential impact on the deployment of software-defined smart grid (SD-SG).
Software-defined networking (SDN) has enabled elastic networking and resource distribution in cloud computing. The centralization and separation of the Control Plane also offers a high degree of network configurability and management, which can be used to mitigate and manage threats to the network. Space communication networks have historically been restricted and circuit switching in these networks has been a manual process. This study evaluates the potential role of SDN in space communication networks from a networking security standpoint. The evaluation covers the networking security needs of spacecraft missions and their associated assets. The results from the evaluation lead to a risk assessment that identifies vulnerabilities in an SDN-based communications architecture. Security challenges introduced into the network from integrating SDN are also considered. A risk register summarizes the severity of the attack outcomes, as well as occurrence likelihood. The study identifies Denial-of-Service (DoS) attacks as a new threat (presently unmitigated by existing security controls) that would be prevalent in an SDN-based space communication environment. A Mininet-based emulation testbed is built to demonstrate the susceptibility of spacecraft flight software to a flooding DoS attack when on an interconnected SDN-managed network. This type of attack would be highly consequential to mission assets, and therefore SDN-based space communications would need to be resilient to such attacks. Future work will need to be performed to fully characterize DoS attack methods that can apply to the space communication scenario, as well as to devise a comprehensive DoS-resilient solution.
Parallel Discrete Events Simulation (PDES) is becoming increasingly important to lab efforts in security and intelligence. It is used to model complex asynchronous systems such as computer networks, satellite systems, vehicular traffic, and human performance. Uncertainty Quantification (UQ) techniques have become a mainstay of Verification and Validation (V&V) efforts on physics simulations. However, PDES models are very different from traditional physics simulations, and research into UQ techniques for PDES is in its infancy. It is not clear which traditional UQ techniques can be applied to PDES, or what new techniques will need to be developed. The goal of this project was to identify existing UQ techniques that can be applied to PDES, and to develop new techniques as necessary. The project implemented or developed techniques to handle issues that do not appear in traditional physics simulations, but are common among PDES, including sampling techniques for high-dimensional homogenous inputs, response surfaces for high-variance heteroskedastic output, and characterization of skewed output distributions. These are foundational UQ techniques that must be used in any complete UQ analysis (Tong 2018).
A Quantum Path Forward. Today, many scientific experts recognize that building and scaling quantum-protected and enhanced communication networks are among the most important technological frontiers of the 21st century. The international research community perceives the construction of a first prototype global quantum network-the Quantum Internet-to be within reach over the next decade. In February 2020, the U.S Department of Energy (DOE)'s Office of Advanced Scientific Computing Research hosted the Quantum Internet Blueprint workshop to define a potential roadmap toward building the first nationwide quantum Internet. The workshop participants included representatives from DOE national laboratories, universities, industry, and other U.S. agencies with serious interests in quantum networking. The goal was to provide an outline of the essential research needed, detail any engineering and design barriers, and suggest a path forward to move from today's limited local network experiments to a viable, secure quantum Internet.
As any mechanical system ages, broken or outdated parts must be replaced; nuclear power plants (NPPs) are no different. The average age of a NPP in the United States' aging fleet of commercial reactors is 35 years, with many of these plants operating under extensions of their original licenses. These plants, originally designed in the 1960's and 1970's, are controlled by analog instrumentation and control (I and C) systems, and have since been upgraded (to varying degrees) to hybrid analog-digital systems. As these NPPs are upgraded to continue operating and to meet more stringent safety requirements imposed by the Nuclear Regulatory Commission (NRC), the implementation of digital systems to monitor and run the power plant introduces new vulnerabilities that must be addressed. The main objectives of a vulnerability assessment (VA) are to identify, quantify, and prioritize all of the susceptibilities inherent in a system. This allows for all weaknesses to be analyzed, and for the most serious concerns to be addressed first. Traditional VA methodologies deal with the analysis of physical systems associated with the NPP; with the introduction of digital control systems and computer networks, these methodologies must be expanded to include these fundamentally different systems and vulnerability concerns. Digital systems have been used in NPPs since the 1980's, but only for non-safety control systems; attacks on these systems were not deemed consequential, and no dedicated VA methodology was required. However, 'all new NPPs are being designed with integrated digital instrumentation and control systems as the backbone of protection, controls, alarms, and display and monitoring'. This gives rise to new vulnerabilities such as disrupted data displays, the suppression of critical alarms, or unauthorized access to secure systems from connected networks. The NRC released formal cybersecurity regulations in March 2009 (10 CFR 73.54), as well as a guide for the program in January 2010 (RG 5.71). However, the regulations and guide provide limited insight on how to identify these vulnerabilities; the focus is on remediating them once found. Hence, there is a need for a comprehensive, systematic methodology to conduct a VA on digital computer and communications and network systems. In this paper, we review traditional VA methodologies and discuss relevant cases. Then we discuss challenges to vulnerabilities within the context of modernization of the fleet and what needs to be done to address this issue.
My job title is IT Security support for the Spaceport Command & Control System Development. As a cyber‐security analyst it is my job to ensure NASA's information stays safe from cyber threats, such as, viruses, malware and denial-of-service attacks by establishing and enforcing system access controls. Security is very important in the world of technology and it is used everywhere from personal computers to giant networks ran by Government agencies worldwide. Without constant monitoring analysis, businesses, public organizations and government agencies are vulnerable to potential harmful infiltration of their computer information system. It is my responsibility to ensure authorized access by examining improper access, reporting violations, revoke access, monitor information request by new programming and recommend improvements. My department oversees the Launch Control System and networks. An audit will be conducted for the LCS based on compliance with the Federal Information Security Management Act (FISMA) and The National Institute of Standards and Technology (NIST). I recently finished analyzing the SANS top 20 critical controls to give cost effective recommendations on various software and hardware products for compliance. Upon my completion of this internship, I will have successfully completed my duties as well as gain knowledge that will be helpful to my career in the future as a Cyber Security Analyst.
The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.
The use of Grid computing environments is growing in popularity. A Grid computing environment is primarily a wide area network that encompasses multiple local area networks, where some of the local area networks are managed by different organizations. A Grid computing environment also includes common interfaces for distributed computing software so that the heterogeneous set of machines that make up the Grid can be used more easily. The other key feature of a Grid is that the distributed computing software includes appropriate security technology. The focus of most Grid software is on the security involved with application execution, file transfers, and other remote computing procedures. However, there are other important security issues related to the management of a Grid and the users who use that Grid. This note discusses these additional security issues and makes several suggestions as how they can be managed.
Some goals of this network are as follows: Extend U.S. technological leadership in high performance computing and computer communications; Provide wide dissemination and application of the technologies both to the speed and the pace of innovation and to serve the national economy, national security, education, and the global environment; and Spur gains in the U.S. productivity and industrial competitiveness by making high performance computing and networking technologies an integral part of the design and production process. Strategies for achieving these goals are as follows: Support solutions to important scientific and technical challenges through a vigorous R and D effort; Reduce the uncertainties to industry for R and D and use of this technology through increased cooperation between government, industry, and universities and by the continued use of government and government funded facilities as a prototype user for early commercial HPCC products; and Support underlying research, network, and computational infrastructures on which U.S. high performance computing technology is based.
With the adoption of Distributed Energy Resource (DER) interoperability standards, common communication protocols are now being deployed between power system operators and DER devices. In 2018, a revision to the US interconnection and interoperability standard, Institute of Electrical and Electronics Engineers (IEEE) Std. 1547, required DER equipment to have an IEEE 2030.5, IEEE 1815, or SunSpec Modbus communication exchange interface. This change supports the future transition to secure connection and exchange of information between the DER equipment and implementing parties, such as grid operators. Adoption of standardized communication protocols and associated information models is a critical step toward interoperability between power system operators and DER, such as photovoltaic (PV) and energy storage systems. However, security requirements for these standardized communication protocols are not comprehensive, resulting in non-standard and vendor-specific implementation that may leave DER equipment susceptible to cyberattacks. This paper examines the data-in-flight security requirements for standardized DER communication protocols, per IEEE 1547-2018 revision, as it relates to device authentication, key management, and encryption. The state of the art for these security features is also explored, addressing their impact on communication and performance of low-cost single board computers, which are typical of DER devices. In conclusion, a recommendation is provided to adopt a common set of communication requirements, which are intended to achieve interoperability and implement data security over DER network pathways, while ensuring reliable, secure, and real-time information delivery.
Automated fault management is at the forefront of next-generation optical communication networks. The increase in complexity of modern networks has triggered the need for programmable and software-driven architectures to support the operation of agile and self-managed systems. In these scenarios, the European Telecommunications Standards Institute zero-touch network and service management approach is imperative. The need for machine learning algorithms to process the large volume of telemetry data brings safety concerns as distributed cloud-computing solutions become the preferred approach for deploying reliable communication network automation. This paper’s contribution is twofold. First, we propose a simple yet effective method to guarantee the confidentiality of the telemetry data based on feature scrambling. The method allows the operation of third-party computational services without direct access to the full content of the collected data. Additionally, the effectiveness of four unsupervised machine learning algorithms for soft-failure detection is evaluated when applied to the scrambled telemetry data. The methods are based on factor analysis, principal component analysis, nonlinear principal component analysis, and singular value decomposition. Most dimensionality reduction algorithms have the common property that they can maintain similar levels of fault classification performance while hiding the data structure from unauthorized access. Evaluations of the proposed algorithms demonstrate this capability.
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The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.
Oak Ridge National Laboratory (ORNL) is leveraging its established capabilities and subject matter expertise in data curation, governance, management, national security, and risk assessment and mitigation to support the US Department of Energy (DOE) Grid Modernization Initiative. Using standards modeled by the National Institute of Standards and Technology (NIST), the Data Curation Network (DCN), the Oak Ridge Leadership Computing Facility (OLCF), and other leading organizations in the fields of energy research, high-performance computing, and national and homeland security, ORNL seeks to provide a federated approach to research data discovery, use, and interoperability.
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In many areas of constrained optimization, representing all possible constraints that give rise to an accurate feasible region can be difficult and computationally prohibitive for online use. Satisfying feasibility constraints becomes more challenging in high-dimensional, non-convex regimes which are common in engineering applications. A prominent example that is explored in the manuscript is the security-constrained optimal power flow (SCOPF) problem, which minimizes power generation costs, while enforcing system feasibility under contingency failures in the transmission network. In its full form, this problem has been modeled as a nonlinear two-stage stochastic programming problem. In this work, we propose a hybrid structure that incorporates and takes advantage of both a high-fidelity physical model and fast machine learning surrogates. Neural network (NN) models have been shown to classify highly non-linear functions and can be trained offline but require large training sets. In this work, we present how model-guided sampling can efficiently create datasets that are highly informative to a NN classifier for non-convex functions. We show how the resultant NN surrogates can be integrated into a non-linear program as smooth, continuous functions to simultaneously optimize the objective function and enforce feasibility using existing non-linear solvers. Overall, this allows us to optimize instances of the SCOPF problem with an order of magnitude CPU improvement over existing methods.