Engineering topics

Yund, Walter

Publications and source records attributed to Yund, Walter.

4 records

DOE OSTI2022

Scalable hierarchical abnormality localization in cyber-physical systems

A cyber-physical system may have monitoring nodes that generate a series of current monitoring node values over time that represent current operation of the system. A hierarchical abnormality localization computer platform accesses a multi-level hierarchy of elements, and elements in a first level of the hierarchy are associated with elements in at least one lower level of the hierarchy and at least some elements may be associated with monitoring nodes. The computer platform may then determine, based on feature vectors and a decision boundary, an abnormality status for a first element in the highest level of the hierarchy. If the abnormality status indicates an abnormality, the computer platform may determine an abnormality status for elements, associated with the first element, in at least one level of the hierarchy lower than the level of the first element. These determinations may be repeated until an abnormality is localized to a monitoring node.

Abbaszadeh, Masoud↗

DOE OSTI2022

Cyber Physical Protection for Natural Gas Compression

The secure transport of natural gas through North American pipelines is vital for both home and industrial purposes. GE in collaboration with Baker Hughes and Idaho National Laboratory, completed a US Department of Energy grant program to develop a new cyber-physical protection system that monitors the large compressor stations used to boost pressure and maintain proper gas flow. Algorithms were developed to detect the presence of a cyber-attack that impacts the compressor station physical processes, locate the critical functions being manipulated, and potentially neutralize the attack allowing continued operations. The technology was successfully demonstrated at an operating compressor facility located in New York state.

03 NATURAL GAS↗

DOE OSTI2022

Cyber-Attack Detection and Accommodation for the Energy Delivery System

The goals of this project were to create a software system with a suite of key algorithms for cyber-attack detection and accommodation providing domain layer protection for critical power generation assets. Example assets included gas and steam turbines, heat recovery steam generators, and electrical generators. The aggressive algorithm goals were aimed at reducing the false positive rates in threat detection to <1% using learnings from many evolving disciplines (power turbine and generator physics, power system modeling, modern control theory, system identification, machine learning, deep learning, mathematics and data science). Additional goals for the algorithms involved localizing threats on-the-fly to know in which monitoring node the effects of attacks are present, and then providing accommodation to keep the system running uninterrupted much of the time in the presence of the attack. Accommodation had a performance goal of providing resiliency when up to 50% of monitoring nodes are in an attack state.

cybersecurity, cyber-physical↗

DOE OSTI2021

Local and global decision fusion for cyber-physical system abnormality detection

Monitoring nodes may generate a series of current monitoring node values over time representing current operation of a cyber-physical system. A decision fusion computer platform may receive, from a local status determination module, an indication of whether each node has an initial local status of “normal”/“abnormal” and a local certainty score (with higher values of the local certainty score representing greater likelihood of abnormality). The computer platform may also receive, from a global status determination module, an indication of whether the system has an initial global status of “normal”/“abnormal” and a global certainty score. The computer platform may output, for each node, a fused local status of “normal” or “abnormal,” at least one fused local status being based on the initial global status. The decision fusion computer platform may also output a fused global status of “normal” or “abnormal” based on at least one initial local status.

Abbaszadeh, Masoud↗