An Experimental Exploration of the Impact of Host-Level Packet Loss on Network Intrusion Detection

Autor:	Carlos J. Mateo, Robert J. Hammell, Sidney C. Smith, Kin W. Wong
Rok vydání:	2016
Předmět:	Computer science Network security business.industry Real-time computing Packet loss rate Intrusion detection system computer.software_genre Measure (mathematics) Kernel (linear algebra) Packet loss Network intrusion detection Data mining business computer Host (network)
Zdroj:	2016 Cybersecurity Symposium (CYBERSEC).
Popis:	In this paper we consider the problem of host-level packet loss (HLPL) as it applies to network intrusion detection. We explore two research questions: 1) is the manifestation of HLPL sufficiently regular to allow an algorithm to be developed to model it? and 2) is the impact of HLPL on network intrusion detection performance sufficiently regular to allow a formula to be developed that will predict the effect? We constructed two experimental environments to allow us to measure the manifestation of HLPL and the impact of HLPL. We graphed the packet loss rate against the alert loss rate. We used nonlinear regression analysis to produce a model with an adjusted R squared value close enough to 1 for us to answer both of our research questions in the affirmative.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::22e6042a2d813c7938eab59718d0b193 https://doi.org/10.1109/cybersec.2016.010 Zobrazit plný text záznamu