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Computer security / Data mining / Statistics / Spamming / Anomaly detection / Intrusion detection system / Network intrusion detection system / Misuse detection / Snort / Computer network security / Data security / Computing


Outside the Closed World: On Using Machine Learning For Network Intrusion Detection Robin Sommer International Computer Science Institute, and Lawrence Berkeley National Laboratory
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Document Date: 2010-03-05 21:14:30


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File Size: 158,47 KB

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Bayesian / /

Company

Amazon / DARPA/Lincoln Labs / Netflix / Google / SRI International / Lawrence Berkeley National Laboratory / /

Country

United States / /

Event

Person Communication and Meetings / /

Facility

Vern Paxson International Computer Science Institute / University of New Mexico / Lawrence Berkeley National Laboratory / On Using Machine Learning For Network Intrusion Detection Robin Sommer International Computer Science Institute / University of Minnesota / University of California / /

IndustryTerm

detection systems / typical client systems / machine learning algorithms / personal communications / web server compromise / recommendation systems / product recommendation systems / neural networks / machine learning tools / anomaly-detection systems / machine-learning algorithm / network intrusion detection systems / unknown web server exploit / similar products / inappropriate tool / adversarial environment such systems / low-latency real-time detection / less-than-ideal solutions / definition such systems / operational networks / product recommendations systems / anomaly detection technology / Internet traffic / anomaly detection systems / web servers / backbone network / neural network / particular web browser / laboratory network / web-based attacks / identified using tools / machine learning algorithm / Internet Computing / machine learning systems / genetic algorithms / optical character recognition systems / network operator / web server / machine learning applications / machine-learning tools / signature systems / appropriate tool / /

Movie

Mind the Gap / /

Organization

Pentagon / U.S. Department of Energy / National Science Foundation / University of California / Berkeley / office of Advanced Scientific Computing Research / Using Machine Learning For Network Intrusion Detection Robin Sommer International Computer Science Institute / office of Science / Vern Paxson International Computer Science Institute / University of New Mexico / Air Force / University of Minnesota / /

Person

Denning / Gerald Friedland / SING M ACHINE / Lawrence Berkeley / Duda / Greg Linden / /

Position

Intrusion-Detection Model / Linguist / author / Director / straight-forward / representative / analyst / /

ProvinceOrState

Minnesota / New Mexico / California / /

PublishedMedium

Machine Learning / IEEE Transactions on Software Engineering / /

Technology

radiation / specific machine-learning algorithm / machine learning algorithms / Machine Translation / machine learning algorithm / peer-to-peer / OCR technology / P2P / optical character recognition / Machine Learning / automatic language translation / application protocols / OCR / neural network / anomaly detection technology / HTTP / simulation / VOIP / web server / /

URL

“Amazon.com / /

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