Unsupervised Online Anomaly Detection to Identify Cyber-Attacks on Internet Connected Photovoltaic System Inverters.
Abstract not provided.
SEARCH · Engineering Papers
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.
Abstract not provided.
Explore the source record for details and available documents.
Not provided.
Not Available
Not Available
The next-generation of high-performance networks being developed in DOE communities are critical for supporting current and emerging data-intensive science applications. The goal of this project is to investigate multi-domain network status sampling techniques and tools to measure/analyze performance, and thereby provide “network awareness” to end-users and network operators in DOE communities. We leverage the infrastructure and datasets available through perfSONAR, which is a multi-domain measurement framework that has been widely deployed in high-performance computing and networking communities; the DOE community is a core developer and the largest adopter of perfSONAR. Our investigations include development of semantic scheduling algorithms, measurement federation policies, and tools to sample multi-domain and multi-layer network status within perfSONAR deployments. We validate our algorithms and policies with end-to-end measurement analysis tools for various monitoring objectives such as network weather forecasting, anomaly detection, and fault-diagnosis. In addition, we develop a multi-domain architecture for an enterprise-specific perfSONAR deployment that can implement monitoring-objective based sampling and that adheres to any domain-specific measurement policies.
The objective of this project is to provide novel and fast reduced-order models for onboard computation at sensor nodes for real-time analysis. The approach will require that LANL perform high-fidelity numerical simulations, construct simple reduced-order models (ROMs) using machine learning and signal processing algorithms, and use real-time data analysis for ROMs and compressive sensing at sensor nodes.
Russia has emerged as an exemplar of an innovative and experimental – though not always completely consistent or successful – alternative approach to information manipulation and control that differs significantly from the more-often discussed Chinese “Great Firewall” system and other approaches with an emphasis on systemic technical censorship. The Russian model relies on a mix of less overt, more plausibly deniable, legalistic, and often non-technical mechanisms to manipulate online information flows, narratives, and framings, to affect and shape public opinion without resort to universal censorship. The government uses surveillance, a panoply of vague laws, the prosecution or censorship of exemplars, proxy actors and hard to track extra-legal pressures, hacking and leaks, and a heavy emphasis on content production and manipulation to influence narratives and shape public opinion. This model for the domestic control of information not only fits with Russia’s own political system, but is likely to prove more resonant and easier to emulate across many other countries in which a systematic-censorship approach is not technologically or politically feasible. The learning and experimentation involved in this type of domestic information manipulation also has direct applicability to the use of information operations in international political and military competition. The future of this model will likely depend on continuing innovation, not least on the leveraging of advances in artificial intelligence and big data analysis. If successful, however, this might look very different from the future of information control in China – and have significantly different repercussions for democracies and the international system.
Abstract not provided.
Abstract not provided.
Abstract not provided.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Despite technical advances in efficiency, devices in standby continue to consume up to 16% of residential electricity. Finding practical, cost-effective reductions is difficult. While the per-unit power consumption has fallen, the number of units continuously drawing power continues to grow. This work reviews a family of technologies that can eliminate standby consumption in many types of electrical plug loads. It also investigates several solutions in detail and develops prototypes. First, burst mode and sleep transistors are established as building blocks for zero-standby solutions. This work then studies the application of two types of wake-up signals. The first is from an optical transmission, and is applicable to remote-controlled devices with a line-of-sight activation, such as set-top boxes, ceiling fans, and motorized curtains. The second is from a wake-up radio, and is applicable to any wireless products. No single technology will address all standby power situations; however, these emerging solutions appear to have broad applicability to save standby energy in miscellaneous plug loads.