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DOE OSTI · 1999758

Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report)

Lagos, Leonel·Upadhyay, Himanshu·Zhao, Wenbing·Joshi, Santosh
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Abstract

Secure Data Logging and Processing with Blockchain and Machine Learning (ML) research is focused on the development of a platform to securely log and process sensor data in fossil power plants. The platform integrates two emerging technologies, blockchain and ML, and incorporates several innovative mechanisms to ensure the integrity, reliability, and resiliency of power systems. The goal is to protect the power plant from various cyberattacks such as false data injection and denial of service attacks using these technologies. The research goal was enabled by the following Research Project Objectives: 1) Secure authentication and identity verification of sensor nodes, actuators, and other equipment within a network. 2) Development of mechanisms that ensure only data sent by legitimate sensors are accepted and stored in the data repository. 3) Development of data aggregation methodologies using ML / Deep Learning (DL) algorithms to minimize noise / faulty data. 4) Implementation of the blockchain technologies to provide data security using secured IOTA framework & nodes.

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20 FOSSIL-FUELED POWER PLANTS97 MATHEMATICS AND COMPUTINGBlockchainMachine LearningPower PlantSensors

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Lagos, Leonel, Upadhyay, Himanshu, Zhao, Wenbing, Joshi, Santosh. 2023-04-30. Secure Data Logging and Processing with Blockchain and Machine Learning (Final Report). https://doi.org/10.2172/1999758

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