Network security metrics: From known vulnerabilities to zero day attacks

Lingyu Wang, Mengyuan Zhang, Anoop Singhal

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

Abstract

Network Secunetwork security metric enables the direct measurement of the relative effectiveness of different security solutions. The results thus provide quantifiable evidences to assist security practitioners in choosing among those security solutions, which makes network security hardening a science rather than an art. The development of network security metrics has evolved from focusing on known vulnerabilities to considering also unknown zero day attacks. This chapter reviews the challenges and solutions in designing network security metrics for both known and unknown threats. Specifically, we first examine how CVSS scores may be combined based on attack graphs to measure the overall threat of residue vulnerabilites; we then estimate the resilience of networks against unknown vulnerabilities by counting the number of such vulnerabilities along the shortest attack path; finally, we model the effect of diversity on network security with respect to zero day attacks.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages450-469
DOIs
Publication statusPublished - 2018
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Funding

The author with Concordia University was partially supported by the Natural Sciences and Engineering Research Council of Canada under Discovery Grant N01035 and by the National Institutes of Standard and Technology under grant 60NANB16D287. Acknowledgements. The author with Concordia University was partially supported by the Natural Sciences and Engineering Research Council of Canada under Discovery Grant N01035 and by the National Institutes of Standard and Technology under grant 60NANB16D287.

FundersFunder number
National Institute of Standards and Technology
Natural Sciences and Engineering Research Council of CanadaN01035, 60NANB16D287

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