Anzeige
Erschienen in:
2014 | OriginalPaper | Buchkapitel
Modeling Network Diversity for Evaluating the Robustness of Networks against Zero-Day Attacks
verfasst von : Lingyu Wang, Mengyuan Zhang, Sushil Jajodia, Anoop Singhal, Massimiliano Albanese
Erschienen in: Computer Security - ESORICS 2014
Verlag: Springer International Publishing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
The interest in diversity as a security mechanism has recently been revived in various applications, such as Moving Target Defense (MTD), resisting worms in sensor networks, and improving the robustness of network routing. However, most existing efforts on formally modeling diversity have focused on a single system running diverse software replicas or variants. At a higher abstraction level, as a global property of the entire network, diversity and its impact on security have received limited attention. In this paper, we take the first step towards formally modeling network diversity as a security metric for evaluating the robustness of networks against potential zero day attacks. Specifically, we first devise a biodiversity-inspired metric based on the effective number of distinct resources. We then propose two complementary diversity metrics, based on the least and the average attacking efforts, respectively. Finally, we evaluate our algorithm and metrics through simulation.