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» Using Unsupervised Learning for Network Alert Correlation
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AI
2008
Springer
13 years 11 months ago
Using Unsupervised Learning for Network Alert Correlation
Alert correlation systems are post-processing modules that enable intrusion analysts to find important alerts and filter false positives efficiently from the output of Intrusion...
Reuben Smith, Nathalie Japkowicz, Maxwell Dondo, P...
NDSS
2005
IEEE
13 years 10 months ago
Enriching Intrusion Alerts Through Multi-Host Causality
Current intrusion detection systems point out suspicious states or events but do not show how the suspicious state or events relate to other states or events in the system. We sho...
Samuel T. King, Zhuoqing Morley Mao, Dominic G. Lu...
COMCOM
2006
88views more  COMCOM 2006»
13 years 4 months ago
Using attack graphs for correlating, hypothesizing, and predicting intrusion alerts
To defend against multi-step intrusions in high-speed networks, efficient algorithms are needed to correlate isolated alerts into attack scenarios. Existing correlation methods us...
Lingyu Wang, Anyi Liu, Sushil Jajodia
KES
2006
Springer
13 years 4 months ago
Alertness Assessment Using Data Fusion and Discrimination Ability of LVQ-Networks
To track the alertness changes of 14 subjects during a night driving simulation study traditional alertness measures such Visual Analog Sleepiness Scale, Alpha Attenuation Test (AA...
Udo Trutschel, David Sommer, Acacia Aguirre, Todd ...
IJNSEC
2006
132views more  IJNSEC 2006»
13 years 4 months ago
Alert Correlation for Extracting Attack Strategies
Alert correlation is an important technique for managing large the volume of intrusion alerts that are raised by heterogenous Intrusion Detection Systems (IDSs). The recent trend ...
Bin Zhu, Ali A. Ghorbani