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DOE OSTI · 2587250

Reactor System Facility Modification to Detect Compromised Human Machine Interfaces

Abstract

This study focuses on a multi-layered Industrial Control System (ICS)/Operational Technology (OT) security architecture to aid in the discovery and mitigation of compromised Human Machine Interface (HMI)/Instrumentation & Control (I&C) based systems for modifying a prototypical reactor condition test facility called the Flowing Autoclave System (FAS) at Idaho National Laboratory (INL). This is achieved through a three-layered combination of network security solutions, hash-based algorithms, and blockchain technologies. Hash algorithms are mathematical functions used to generate a predetermined set of fixed-length values. They are widely used in computer security to verify the integrity of system information and data, both on a local network and the wider internet. Even small amounts of unauthorized system modification will cause the hash algorithm to output a set of characters that deviate significantly from its original value. Assisting secure hash functions, blockchain technology is a secure and distributed technology used to provide an immutable set of records replicated on all devices within a decentralized network. Blockchain offers a cost-effective solution to detect system compromise by providing a traceable breadcrumb trail of all network activity and data modification happening on a system. If both are used in conjunction with network monitoring tools, the integration of this three-pronged approach can become an asset in detecting suspected system compromises before any real damage can occur.

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BibTeXRIS

Arevalo Macasaet, Nathaniel Lewis [Idaho National Laboratory (INL), Idaho Falls, ID (United States)], Bhowmik, Palash Kumar [Idaho National Laboratory (INL), Idaho Falls, ID (United States)] (ORCID:0000000335717805), Skifton, Richard S. [Idaho National Laboratory (INL), Idaho Falls, ID (United States)]. 2025-07-01. Reactor System Facility Modification to Detect Compromised Human Machine Interfaces. https://doi.org/10.2172/2587250

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