[en] Moving Target Defense (MTD) presents dynamically changing attack surfaces and system configurations to attackers. This approach decreases the success probabilities of attacks and increases attacker's workload since she must continually re-assess, re-engineer and re-launch her attacks. Existing research has provided a number of MTD techniques but approaches for gaining situational awareness and deciding when/how to apply these techniques are not well studied. In this paper, we present a conceptual framework that closely integrates a set of models with the system and obtains up-to-date situational awareness following the OODA loop methodology. To realize the framework, as the first step, we propose a modelling approach that provides insights about the dynamics between potential attacks and defenses, impact of attacks and adaptations on the system, and the state of the system. Based on these models, we demonstrate techniques to quantitatively assess the effectiveness of MTD and show how to formulate decision-making problems.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
JHAWAR, Ravi ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
MAUW, Sjouke ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Model-driven situational awareness for moving target defense
Date de publication/diffusion :
2017
Nom de la manifestation :
16th European Conference on Cyber Warfare and Security (ECCWS'17)
Lieu de la manifestation :
Dublin, Irlande
Date de la manifestation :
June 29-30 2017
Manifestation à portée :
International
Titre de l'ouvrage principal :
Proc. 16th European Conference on Cyber Warfare and Security
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