TY - GEN
T1 - Modeling network diversity for evaluating the robustness of networks against zero-day attacks
AU - Wang, Lingyu
AU - Zhang, Mengyuan
AU - Jajodia, Sushil
AU - Singhal, Anoop
AU - Albanese, Massimiliano
PY - 2014
Y1 - 2014
N2 - 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. © 2014 Springer International Publishing Switzerland.
AB - 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. © 2014 Springer International Publishing Switzerland.
UR - https://www.scopus.com/pages/publications/84906511087
UR - https://www.scopus.com/inward/citedby.url?scp=84906511087&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11212-1_28
DO - 10.1007/978-3-319-11212-1_28
M3 - Conference contribution
SN - 9783319112114
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 494
EP - 511
BT - Computer Security, ESORICS 2014 - 19th European Symposium on Research in Computer Security, Proceedings
PB - Springer Verlag
T2 - 19th European Symposium on Research in Computer Security, ESORICS 2014
Y2 - 7 September 2014 through 11 September 2014
ER -