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Communication Dans Un Congrès Année : 2017

A Framework for Moving Target Defense Quantification

Warren Connell
  • Fonction : Auteur
  • PersonId : 1023785
Massimiliano Albanese
  • Fonction : Auteur
  • PersonId : 1023786
Sridhar Venkatesan
  • Fonction : Auteur
  • PersonId : 1023787

Résumé

Moving Target Defense (MTD) has emerged as a game changer in the security landscape, as it can create asymmetric uncertainty favoring the defender. Despite the significant work done in this area and the many different techniques that have been proposed, MTD has not yet gained widespread adoption due to several limitations. Specifically, interactions between multiple techniques have not been studied yet and a unified framework for quantifying and comparing very diverse techniques is still lacking. To overcome these limitations, we propose a framework to model how different MTD techniques can affect the information an attacker needs to exploit a system’s vulnerabilities, so as to introduce uncertainty and reduce the likelihood of successful attacks. We illustrate how this framework can be used to compare two sets of MTDs, and to select an optimal set of MTDs that maximize security within a given budget. Experimental results show that our approach is effective.
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hal-01648997 , version 1 (27-11-2017)

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Warren Connell, Massimiliano Albanese, Sridhar Venkatesan. A Framework for Moving Target Defense Quantification. 32th IFIP International Conference on ICT Systems Security and Privacy Protection (SEC), May 2017, Rome, Italy. pp.124-138, ⟨10.1007/978-3-319-58469-0_9⟩. ⟨hal-01648997⟩
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