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» LIDS: Learning Intrusion Detection System
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ACMSE
2006
ACM
13 years 9 months ago
Hybrid intelligent systems for network security
Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportu...
J. Lane Thames, Randal Abler, Ashraf Saad
RAID
1999
Springer
13 years 11 months ago
Combining Knowledge Discovery and Knowledge Engineering to Build IDSs
We have been developing a data mining (i.e., knowledge discovery) framework, MADAM ID, for Mining Audit Data for Automated Models for Intrusion Detection [LSM98, LSM99b, LSM99a]. ...
Wenke Lee, Salvatore J. Stolfo
AI
2008
Springer
14 years 1 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...
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
14 years 8 months ago
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Jude W. Shavlik, Mark Shavlik
NDSS
2005
IEEE
14 years 1 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...