Bayesian Attack Model (BAM) User Story
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sandia National Laboratories (SNL-CA), Livermore, CA (United States)
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).
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE Office of Cybersecurity, Energy Security, and Emergency Response (CESER); USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- NA0003525
- OSTI ID:
- 2589620
- Report Number(s):
- SAND--2025-11801R; 1786445
- Country of Publication:
- United States
- Language:
- English
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