SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
NNSS Area 5 RWMS Groundwater and Leachate Monitoring Report for RCRA Permit NEV HW0101
Explore the source record for details and available documents.
Unauthorized data exfiltrations from both insiders and outsiders are costly and damaging. Network communication resources can be used for transporting data illicitly out of the enterprise or cloud. Combined with built-in malware copying utilities, we define this as comprising the Data Exfiltration Surface (DXS). For securing valuable data, it is desirable to reduce the DXS and maintain controls on the egress points. Our approach is to host the data in a protected enclave that includes novel software Data Diode (SDD) installed on a secured, border gateway. The SDD allows copying data into the enclave systems but denies data from being copied out. Simultaneously, it permits remote access with remote desktop and console applications. Our tests demonstrate that we are able to effectively reduce the DXS and we are able to protect data from being exfiltrated through the use of the SDD.
Data libraries are essential for the characterization of the facility and provide the documented input which enables the facility assessment results and subsequent conclusions. Data Libraries are historical, verifiable, quantified, and applicable collections of testing data on different types of barriers, sensors, cameras, procedures, and/or personnel. Data libraries are developed and maintained as part of any assessment program or process. Data is collected during the initial stages of facility characterization to aid in the model and/or simulation development process. Data library values may also be developed through the use of state testing centers and/or site resources by testing different types of barriers, sensors, cameras, procedures, and/or personnel. If no data exists, subject matter expert opinion and manufacturer's specifications/ testing values can be the basis for initially assigning values, but are generally less reliable and lack appropriate confidence measures. The use of existing data libraries that have been developed by a state testing organization reduces the assessment costs by establishing standard delay, detection and assessment values for use by multiple sites or facilities where common barriers and alarms systems exist.
To incorporate the superiority of both stochastic and robust approaches, a data-driven stochastic optimization is employed to solve the security-constrained unit commitment model. This approach makes the most use of the historical data to generate a set of possible probability distributions for wind power outputs and then it optimizes the unit commitment under the worst-case probability distribution. However, this model suffers from huge computational burden, as a large number of scenarios are considered. To tackle this issue, a duality-free decomposition method is proposed in this paper. This approach does not require doing duality, which can save a large set of dual variables and constraints, and therefore reduces the computational burden. In addition, the inner max-min problem has a special mathematical structure, where the scenarios have the similar constraint. Thus, the max-min problem can be decomposed into independent sub-problems to be solved in parallel, which further improves the computational efficiency. A numerical study on an IEEE 118-bus system with practical data of a wind power system has demonstrated the effectiveness of the proposal.
This presentation will present a pragmatic security approach that could be used to systems that process large files of data.
The power grid is a complex network connecting electricity providers with their consumers. With an increasing consumer base requiring more resources and the requirement to integrate significant renewable sources, maintaining the network requires new and innovative management solutions. To manage this complexity and provide precise, real-time views of the grid, Phasor Measurement Units (PMUs) are undergoing widespread deployment. These units provide measurements as often as 60 times per second, with an accurate time identifier attached to each reading, enabling real-time monitoring of the network. However, this new capability generates much more data than the current infrastructure is designed to handle. With the expectation that there will eventually be tens of thousands of PMUs monitoring the transmission lines, the power community is looking towards accumulating multiple terabytes of data per day - several orders of magnitude beyond current data acquisition rates. This has led to questions being raised in the power community about whether or not a significant research effort is required to effectively transfer the volume of information generated by these new data streams. This paper answers that question by comparing a worst-case data generation scenario with several alternative networking protocols and historical trends in protocol advancement. Based on this analysis we are able to conclude that transferring the information between the PMUs and the resulting data repositories is feasible. We recognize that there are issues beyond transferring the data that need to be addressed such as effective access to historical data, data transfer latency, cyber security, and data analysis. There is also an extensive engineering trade-off that the power companies will need to make to decide the best mix of networking protocols for their particular PMU deployments, since that requires significant assumptions about proprietary information including deployment cost, deployment schedules, PMU locations, and available resources.
This report describes the radiological Scene Data Fusion (SDF) technology and the potential to apply the SDF technology to a variety of problems related to nuclear non-proliferation, radiological security, and other missions related to the national nuclear security agency and the US government, more broadly. The application space was conceived by both the authors of this report and the many scientists and stakeholders they interviewed. In order to successfully apply the SDF technology to the various applications, further research and development is often necessary and those R&D steps are also outlined herein.
Distribution of interactive multimedia to remote investigators will be required for high quality science on the International Space Station (ISS). The Internet with the World Wide Web (WWW) and the JAVA environment are a good match for distribution of data, video and voice to remote science centers. Utilizing the "open" Internet in a secure manner is the major hurdle in making use of this cost effective, off-the-shelf, universal resource. This paper examines the major security threats to an Internet distribution system for payload data and the mitigation of these threats. A proposed security environment for the Space Station Biological Research Facility (SSBRP) is presented with a short description of the tools that have been implemented or planned. Formulating and implementing a security policy, firewalls, host hardware and software security are also discussed in this paper. Security is a vast topic and this paper can only give an overview of important issues. This paper postulates that a structured approach is required and stresses that security must be built into a network from the start. Ignoring security issues or putting them off until late in the development cycle can be disastrous.
As electric power systems undergo a transformative upgrade with the integration of advanced technologies to enable the smarter electric grid, professionals who work in the area require a new understanding of the evolving complexity of the grid. Cyber Infrastructure for the Smart Electric Grid delivers a comprehensive overview of the fundamental principles of smart grid operation and control, smart grid technologies, including sensors, communication networks, computation, data management, and cyber security, and the interdependencies between the component technologies on which a smart grid's security depends. The book offers readers the opportunity to critically analyze the smart grid infrastructure needed to sense, communicate, compute, and control in a secure way.
The overlap of quantum computing and biomedical research, while less explored, presents significant near-term opportunities. The Department of Energy (DOE) and the National Institutes of Health (NIH) are interested in exploiting the DOE community’s capabilities and expertise in quantum computing to potentially advance biomedical research, targeting fundamental studies of biological and molecular structures, understanding of human health as well as mental and physical disorders and diseases, and deriving insights from clinical data. NIH’s approach to quantum computing is guided by its Strategic Plan for Data Science, emphasizing the importance of findable, accessible, interoperable, and reusable (FAIR) data assets, security and privacy of data, and efficient computing and storage. DOE’s Office of Science (SC), and more specifically the Advanced Scientific Computing Research (ASCR) program, supports quantum information science (QIS) research, contributing to a unique portfolio of quantum computing and communications expertise. This roundtable was assembled to consider the opportunities and challenges in the near-, medium-, and long-term at the intersection of quantum computing, data science, and biomedical research and how these could be addressed through inter-agency collaboration and multi-disciplinary partnerships.
A set of considerations that are pertinent to future international cooperation in the area of synthetic aperture radar (SAR) ground data systems are presented. The considerations are as follows: (1) success of future spaceborne SAR missions will require multi-agency and/or multi-national collaboration; (2) ground processing is typically performed by each agency for their user base; (3) international standards are required to achieve a uniform data product independent of the processing center; (4) to reduce the aggregate cost of the ground data systems, collaboration is required in design and development; (5) effective utilization of the data by an international user community; (6) commercialization of data products; and (7) security of data systems.
A Web application facilitates collaborative development of the ground operations planning document. This will reduce costs and development time for new programs by incorporating the data governance, access control, and revision tracking of the ground operations planning data. Ground Operations Planning requires the creation and maintenance of detailed timelines and documentation. The GOPDb Web application was created using state-of-the-art Web 2.0 technologies, and was deployed as SaaS (Software as a Service), with an emphasis on data governance and security needs. Application access is managed using two-factor authentication, with data write permissions tied to user roles and responsibilities. Multiple instances of the application can be deployed on a Web server to meet the robust needs for multiple, future programs with minimal additional cost. This innovation features high availability and scalability, with no additional software that needs to be bought or installed. For data governance and security (data quality, management, business process management, and risk management for data handling), the software uses NAMS. No local copy/cloning of data is permitted. Data change log/tracking is addressed, as well as collaboration, work flow, and process standardization. The software provides on-line documentation and detailed Web-based help. There are multiple ways that this software can be deployed on a Web server to meet ground operations planning needs for future programs. The software could be used to support commercial crew ground operations planning, as well as commercial payload/satellite ground operations planning. The application source code and database schema are owned by NASA.
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.
Ocean color satellite measurements have yielded valuable information about the base of the marine food web for over 20 years. The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission is building an advanced spectrometer to further refine ecosystem monitoring. Higher spectral resolution data from PACE will enable identification of additional marine biological indicators and their response to multiple stressors to guide sustainable management. Seafood is an important source of protein for a significant number of people. Wild catches cannot match increasing demand and their sustainability is in question. Aquaculture is an ever more important industry to feed the world's population. We share early efforts to engage a community of practice around food security to increase satellite data product use in support of resource management, business decisions, and policy analysis. Understanding the needs of applied scientists as well as non-traditional users of satellite data early in the PACE mission process will improve planning and preparation for a broader user base and hopefully help to mitigate food insecurity.
Not provided.
The Aviation Data Integration System (ADIS) of Ames Research Center has been established to promote analysis of aviation data by airlines and other interested users for purposes of enhancing the quality (especially safety) of flight operations. The ADIS is a system of computer hardware and software for collecting, integrating, and disseminating aviation data pertaining to flights and specified flight events that involve one or more airline(s). The ADIS is secure in the sense that care is taken to ensure the integrity of sources of collected data and to verify the authorizations of requesters to receive data. Most importantly, the ADIS removes a disincentive to collection and exchange of useful data by providing for automatic removal of information that could be used to identify specific flights and crewmembers. Such information, denoted sensitive information, includes flight data (here signifying data collected by sensors aboard an aircraft during flight), weather data for a specified route on a specified date, date and time, and any other information traceable to a specific flight. The removal of information that could be used to perform such tracing is called "deidentification." Airlines are often reluctant to keep flight data in identifiable form because of concerns about loss of anonymity. Hence, one of the things needed to promote retention and analysis of aviation data is an automated means of de-identification of archived flight data to enable integration of flight data with non-flight aviation data while preserving anonymity. Preferably, such an automated means would enable end users of the data to continue to use pre-existing data-analysis software to identify anomalies in flight data without identifying a specific anomalous flight. It would then also be possible to perform statistical analyses of integrated data. These needs are satisfied by the ADIS, which enables an end user to request aviation data associated with de-identified flight data. The ADIS includes client software integrated with other software running on flight-operations quality-assurance (FOQA) computers for purposes of analyzing data to study specified types of events or exceedences (departures of flight parameters from normal ranges). In addition to ADIS client software, ADIS includes server hardware and software that provide services to the ADIS clients via the Internet (see figure). The ADIS server receives and integrates flight and non-flight data pertaining to flights from multiple sources. The server accepts data updates from authorized sources only and responds to requests from authorized users only. In order to satisfy security requirements established by the airlines, (1) an ADIS client must not be accessible from the Internet by an unauthorized user and (2) non-flight data as airport terminal information system (ATIS) and weather data must be displayed without any identifying flight information. ADIS hardware and software architecture as well as encryption and data display scheme are designed to meet these requirements. When a user requests one or more selected aviation data characteristics associated with an event (e.g., a collision, near miss, equipment malfunction, or exceedence), the ADIS client augments the request with date and time information from encrypted files and submits the augmented request to the server. Once the user s authorization has been verified, the server returns the requested information in de-identified form.
Distributed multisensor networks record multiple data streams that can be used as inputs to machine learning models designed to classify operations relevant to proliferation at nuclear reactors. The goal of this work is to demonstrate methods to assess the importance of each node (a single multisensor) and region (a group of proximate multisensors) to machine learning model performance in a reactor monitoring scenario. This, in turn, provides insight into model behavior, a critical requirement of data-driven applications in nuclear security. Using data collected at the High Flux Isotope Reactor at Oak Ridge National Laboratory via a network of Merlyn multisensors, two different models were trained to classify the reactor’s operational state: a hidden Markov model (HMM), which is simpler and more transparent, and a feed-forward neural network, which is less inherently interpretable. Traditional wrapper methods for feature importance were extended to identify nodes and regions in the multisensor network with strong positive and negative impacts on the classification problem. These spatial-importance algorithms were evaluated on the two different classifiers. The classification accuracy was then improved relative to baseline models via feature selection from 0.583 to 0.839 and from 0.811 ± 0.005 to 0.884 ± 0.004 for the HMM and feed-forward neural network, respectively. While some differences in node and region importance were observed when using different classifiers and wrapper methods, the nodes near the facility’s cooling tower were consistently identified as important—a conclusion further supported by studies on feature importance in decision trees. Node and region importance methods are model-agnostic, inform feature selection for improved model performance, and can provide insight into opaque classification models in the nuclear security domain.