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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.
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Securing Vehicle Charging Infrastructure Against Cybersecurity Threats.
Abstract not provided.
EMULATION METHODOLOGY OF PROGRAMMABLE LOGIC CONTROLLERS FOR CYBERSECURITY APPLICATIONS.
Abstract not provided.
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams
Analysis of an organization’s computer network activity is a key component of early detection and mitigation of insider threat, a growing concern for many organizations. Raw system logs are a prototypical example of streaming data that can quickly scale beyond the cognitive power of a human analyst. As a prospective filter for the human analyst, we present an online unsupervised deep learning approach to detect anomalous network activity from system logs in real time. Our models decompose anomaly scores into the contributions of individual user behavior features for increased interpretability to aid analysts reviewing potential cases of insider threat. Using the CERT Insider Threat Dataset v6.2 and threat detection recall as our performance metric, our novel deep and recurrent neural network models outperform Principal Component Analysis, Support Vector Machine and Isolation Forest based anomaly detection baselines. For our best model, the events labeled as insider threat activity in our dataset had an average anomaly score in the 95.53 percentile, demonstrating our approach’s potential to greatly reduce analyst workloads.
US EPA Water Security Test Bed - Water Infrastructure Cybersecurity Research Vision
Virtual tour of the Water Security Test Bed, a joint INL & EPA test bed.
Sequence Embeddings using LSTM Networks: Applications to Cybersecurity.
Abstract not provided.
Emulation Methodology of Programmable Logic Controllers for Cybersecurity Applications.
Abstract not provided.
Cybersecurity Risk Assessment Framework for Externally Exposed Energy Delivery Systems
Securing the energy delivery system (EDS) from complex, nonlinear, and evolving cyber threats requires a complex set of changing and interwoven classes of technologies, policies, relationships, and personnel. One key area in this technological milieu is assessment methodologies to compare information, gathered by a variety of means, about networked devices with publicly known possible threat information about said devices. This information is used to generate risk-based characterizations that allow for the adjudication and proper corresponding management action chains to be assigned.
Information Security for Remote Cybersecurity Inspections of Nuclear Sites
Explore the source record for details and available documents.
MANAGING CYBERSECURITY SUPPLY CHAIN RISKS FOR THE SECURITY OF RADIOACTIVE SOURCES.
Abstract not provided.
Quantum frequency processor for provable cybersecurity
Methods of quantum key distribution include receiving a frequency bin photon at a location, selecting a frequency bin photon quantum key distribution measurement basis, with a quantum frequency processor, performing a measurement basis transformation on the received frequency bin photon so that the frequency bin photon is measurable in the selected frequency bin photon quantum key distribution measurement basis, and detecting the frequency bin photon in the selected quantum key distribution measurement basis and assigning a quantum key distribution key value based on the detection to a portion of a quantum key distribution key. Apparatus and methods for encoding, decoding, transmitting, and receiving frequency bin photons are disclosed.
Recent results from a testbed for the reliability of the digital instrumentation and control systems and cybersecurity in nuclear power plants - 392
Transition from analog to digital instrumentation and control systems requires a systematic study of the modifications, and assessment of their reliability. Such studies are often carried out on a test bed. The test bed developed earlier includes a commercially available triple modular redundant (TMR) programmable logic controller (PLC) for testing not only the reliability of the digital I and C but also the cyber-security of the system during plant operation. This paper reports results of our preliminary analyses carried out using the test bed following the injection of faults mimicking faulty sensors. The fault injection tool generates faulty signals in single or multiple sensors located in the primary loop. These scenarios studied under steady-state operation conditions simulate a bad sensor, a cut wire, noise, etc. The faults injected can lead to information being displayed in the main control room (MCR) to not match the conditions in the plant. In addition to a fault injection module, a result analyzer module is also a part of this testbed. Operator actions can be based on information displayed in the MCR, or they can be informed by the result analyzer. Potential operator actions following these single- or multiple faulty signals are assessed. It is concluded that the result analyzer in some cases can be helpful in guiding operators to make the right decisions. (authors)