ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2412.13964
92
0
v1v2 (latest)

DODGE: Ontology-Aware Risk Assessment via Object-Oriented Disruption Graphs

18 December 2024
Stefano M. Nicoletti
Ernst Moritz Hahn
Mattia Fumagalli
Giancarlo Guizzardi
Marielle Stoelinga
ArXiv (abs)PDFHTML
Main:15 Pages
3 Figures
Bibliography:2 Pages
1 Tables
Abstract

When considering risky events or actions, we must not downplay the role of involved objects: a charged battery in our phone averts the risk of being stranded in the desert after a flat tyre, and a functional firewall mitigates the risk of a hacker intruding the network. The Common Ontology of Value and Risk (COVER) highlights how the role of objects and their relationships remains pivotal to performing transparent, complete and accountable risk assessment. In this paper, we operationalize some of the notions proposed by COVER - such as parthood between objects and participation of objects in events/actions - by presenting a new framework for risk assessment: DODGE. DODGE enriches the expressivity of vetted formal models for risk - i.e., fault trees and at- tack trees - by bridging the disciplines of ontology and formal methods into an ontology-aware formal framework composed by a more expressive modelling formalism, Object-Oriented Disruption Graphs (ODGs), logic (ODGLog) and an intermediate query language (ODGLang). With these, DODGE allows risk assessors to pose questions about disruption propagation, disruption likelihood and risk levels, keeping the fundamental role of objects at risk always in sight.

View on arXiv
@article{nicoletti2025_2412.13964,
  title={ WATCHDOG: an ontology-aWare risk AssessmenT approaCH via object-oriented DisruptiOn Graphs },
  author={ Stefano M. Nicoletti and E. Moritz Hahn and Mattia Fumagalli and Giancarlo Guizzardi and Mariëlle Stoelinga },
  journal={arXiv preprint arXiv:2412.13964},
  year={ 2025 }
}
Comments on this paper