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DOE OSTI · 2589620

Bayesian Attack Model (BAM) User Story

Maccarone, Lee T. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000220230255)·Valme, Romuald [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)]·Anaya, Ted R. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)]
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Abstract

This document presents a user story for the Bayesian Attack Model (BAM) tool designed to aggregate and analyze cyber-attack observables for operational technology (OT) systems. BAM aims to empower cybersecurity analysts by providing a streamlined interface for collecting observable data from various sources, enabling real-time analysis of potential adversary activity. By enhancing the response capabilities of security teams, BAM facilitates risk-informed decision-making and improves organizational security posture. This user story outlines the key functionalities, user interactions, and requirements necessary to successfully integrate BAM with other security information and event management (SIEM) technology and cybersecurity operations centers (CSOCs).

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BibTeXRIS

Maccarone, Lee T. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000220230255), Valme, Romuald [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)], Anaya, Ted R. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States)]. 2025-09-01. Bayesian Attack Model (BAM) User Story. https://doi.org/10.2172/2589620

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