Communication Dans Un Congrès Année : 2025

Revisiting a probabilistic moving target defense strategy to handle attacks against network nodes with multiple resources

Résumé

Traditional cyber defense strategies rely on a linear approach that involves detecting threats, selecting defenses, and mitigating attacks; yet, they struggle with emerging, unrecognized, and advanced threats. In search of a more robust solution, researchers have explored innovative strategies to maintain cybersecurity in a network without prior knowledge of the adversary or the specific attack being executed. One such strategy is known as Moving Target Defense (MTD). Leveraging Bayesian Stackelberg game theory, we establish optimal strategies for the defender and adversary, showcasing how the defender can reduce costs by steering attacks away from higher criticality nodes. This approach helps the defender implement a novel MTD logic model for either diversion or minimization of the attack damages. We use simulation results to show how our approach surpasses previous strategies. Our approach offers improvements in managing a multitude of resources. The new approach, while not addressing the known drawbacks, lays the foundation for more advanced MTD models that can incorporate a more detailed representation of system resources.

Fichier principal
Vignette du fichier
preprint-FICC2025.pdf (1.25 Mo) Télécharger le fichier
preprint-FICC2025 (1).pdf (1.25 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Licence

Dates et versions

hal-05033577 , version 1 (28-07-2025)

Licence

Identifiants

Citer

Jamil Ahmad Kassem, Helena Rifà-Pous, Joaquin Garcia‐alfaro. Revisiting a probabilistic moving target defense strategy to handle attacks against network nodes with multiple resources. Future of Information and Communication Conference (FICC), Apr 2025, Berlin (Germany), Germany. pp.536-554, ⟨10.1007/978-3-031-85363-0_34⟩. ⟨hal-05033577⟩
539 Consultations
237 Téléchargements

Altmetric

Partager

  • More