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Title: Data Ingestion, Analysis, and Situational Awareness Tool

Abstract

The Department of Energy (DOE) requires an effective, automated situational awareness tool for robust and resilient fossil energy power generation. This tool should constantly scan a multitude of sensor data to assess the health of the power plant; recognize malicious behavior and automatically trigger countermeasures to mitigate it; inform operators about intrusions in real time; support both older and newer fossil power infrastructures, individual municipalities, and investor owned utilities; and be compliant with the North American Electric Reliability Corporation (NERC) requirements. To address this need, Physical Optics Corporation (POC) successfully completed a Phase I Small Business Innovation Research (SBIR) project, Data Ingestion, Analysis, and Situational Awareness Tool (DIASAT). DIASAT is a software tool that innovatively integrates an advanced machine learning-based intrusion detection/response system and secure data and commands transfer empowered with blockchain technology. This combination provides the artificial intelligence (AI) needed to detect, provide alerts for, and mitigate various cyber threats that can compromise the operation of fossil power plants in near real time to provide cyber security, data integrity, and resilient fossil energy power generation. During Phase I, an intelligent intrusion detection/prevention system architecture, framework, and algorithms were developed; the metrics that determine the system’s efficacy and performance weremore » identified; and system performance was evaluated. POC demonstrated the feasibility of DIASAT by developing and testing a technology readiness level (TRL)-4 prototype. The simplified prototype (emulating a real fossil energy power plant and network) successfully demonstrated the capability to detect, characterize, and report anomalies and attack patterns in real time using sensor data obtained from an accurate fossil energy power plant emulator. In wrapping up the Phase I effort, POC also designed plans for the enhancement of the intrusion/anomaly detection/protection capabilities of DIASAT and its integration with a fossil energy power plant in Phase II.« less

Authors:
Publication Date:
Research Org.:
Physical Optics Corporation
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1507030
Report Number(s):
DOE-POC-0018785
10196
DOE Contract Number:  
SC0018785
Type / Phase:
SBIR (Phase I)
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
20 FOSSIL-FUELED POWER PLANTS; Cybersecurity, intrusion detection, intrusion prevention, industrial control systems, sensor data acquisition, blockchain, machine learning, smart grid

Citation Formats

Milovanov, Alexander. Data Ingestion, Analysis, and Situational Awareness Tool. United States: N. p., 2019. Web.
Milovanov, Alexander. Data Ingestion, Analysis, and Situational Awareness Tool. United States.
Milovanov, Alexander. Mon . "Data Ingestion, Analysis, and Situational Awareness Tool". United States.
@article{osti_1507030,
title = {Data Ingestion, Analysis, and Situational Awareness Tool},
author = {Milovanov, Alexander},
abstractNote = {The Department of Energy (DOE) requires an effective, automated situational awareness tool for robust and resilient fossil energy power generation. This tool should constantly scan a multitude of sensor data to assess the health of the power plant; recognize malicious behavior and automatically trigger countermeasures to mitigate it; inform operators about intrusions in real time; support both older and newer fossil power infrastructures, individual municipalities, and investor owned utilities; and be compliant with the North American Electric Reliability Corporation (NERC) requirements. To address this need, Physical Optics Corporation (POC) successfully completed a Phase I Small Business Innovation Research (SBIR) project, Data Ingestion, Analysis, and Situational Awareness Tool (DIASAT). DIASAT is a software tool that innovatively integrates an advanced machine learning-based intrusion detection/response system and secure data and commands transfer empowered with blockchain technology. This combination provides the artificial intelligence (AI) needed to detect, provide alerts for, and mitigate various cyber threats that can compromise the operation of fossil power plants in near real time to provide cyber security, data integrity, and resilient fossil energy power generation. During Phase I, an intelligent intrusion detection/prevention system architecture, framework, and algorithms were developed; the metrics that determine the system’s efficacy and performance were identified; and system performance was evaluated. POC demonstrated the feasibility of DIASAT by developing and testing a technology readiness level (TRL)-4 prototype. The simplified prototype (emulating a real fossil energy power plant and network) successfully demonstrated the capability to detect, characterize, and report anomalies and attack patterns in real time using sensor data obtained from an accurate fossil energy power plant emulator. In wrapping up the Phase I effort, POC also designed plans for the enhancement of the intrusion/anomaly detection/protection capabilities of DIASAT and its integration with a fossil energy power plant in Phase II.},
doi = {},
url = {https://www.osti.gov/biblio/1507030}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {4}
}

Technical Report:
This technical report may be released as soon as April 15, 2023
Other availability
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