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Anomaly detection
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#	Item
331	Volume 3, Issue 1, January – December[removed]Machine Learning Methods for Computer Security (Dagstuhl Perspectives Workshop[removed]Anthony D. Joseph, Pavel Laskov, Fabio Roli, J. Doug Tygar, and Blaine Nelson . Add to Reading List Source URL: drops.dagstuhl.de Language: English - Date: 2014-10-16 03:45:30 Machine learning Data security National security Computing Cyberwarfare Malware Anomaly detection Computational learning theory Antivirus software Security Computer security Computer network security
332	Manifesto from Dagstuhl Perspectives Workshop[removed]Machine Learning Methods for Computer Security Edited by Anthony D. Joseph1 , Pavel Laskov2 , Fabio Roli3 , J. Doug Tygar4 , Add to Reading List Source URL: drops.dagstuhl.de Language: English - Date: 2013-12-02 06:59:30 Security Cyberwarfare Computing Data mining Malware Anomaly detection Computational learning theory Application security Supervised learning Computer network security Machine learning Computer security
333	Expectation Failure as a Basis for Agent-Based Model Diagnosis and Mixed Initiative Model Adaptation during Anomalous Plan Execution Add to Reading List Source URL: aaai.org Language: English - Date: 2007-01-30 16:54:12 Economic model Maximum likelihood Likelihood function Anomaly detection Simulation Statistics Estimation theory Statistical theory
334	CONDOR: A Hybrid IDS to Offer Improved Intrusion Detection DAY, David and FLORES, Denys Available from Sheffield Hallam University Research Archive (SHURA) at: http://shura.shu.ac.uk/5246/ Add to Reading List Source URL: shura.shu.ac.uk Language: English - Date: 2013-08-01 09:17:33 Security Intrusion detection system Anomaly detection Anomaly-based intrusion detection system Snort Network intrusion detection system Burglar alarm Network security Malware Computer network security System software Software
335	IAPRS Volume XXXVI, Part 5, Dresden[removed]September[removed]OUTLIER DETECTION IN LASER SCANNER POINT CLOUDS S. Sotoodeh Institute of Geodesy and Photogrammetry, ETHZ, Switzerland [removed] Add to Reading List Source URL: www.isprs.org Language: English - Date: 2012-10-18 13:34:57 Robust statistics Local outlier factor Outlier Anomaly detection Cluster analysis Point cloud Segmentation LOF OPTICS algorithm Statistics Data mining Data analysis
336	Microsoft Word - aaai_final.doc Add to Reading List Source URL: www.aaai.org Language: English - Date: 2008-03-11 15:26:12 Intrusion detection systems Computer security Multi-agent systems Intrusion prevention system Network intrusion detection system Host-based intrusion detection system Anomaly detection Botnet Antivirus software Computer network security System software Computing
337	Network Anomaly Detection Using Autonomous System Flow Aggregates To appear, GLOBECOM[removed]Draft version Thienne Johnson and Loukas Lazos Department of Electrical and Computer Engineering University of Arizona, Tucson, Add to Reading List Source URL: netvue.cs.arizona.edu Language: English - Date: 2014-10-16 13:25:04 Traffic flow Denial-of-service attack Anomaly detection Transmission Control Protocol OSI protocols Computer network security Computing Intrusion detection system
338	Unsupervised Two-Class & Multi-class Support Vector Machines for Abnormal Traffic Characterization [Extended Abstract] † † Add to Reading List Source URL: pam2009.kaist.ac.kr Language: English - Date: 2009-03-31 10:04:15 Statistical classification Data mining Support vector machine Anomaly detection Document classification Unsupervised learning Kernel methods Supervised learning Margin classifier Statistics Machine learning Artificial intelligence
339	Unsupervised Two-Class & Multi-class Support Vector Machines for Abnormal Traffic Characterization [Extended Abstract] † † Add to Reading List Source URL: eprints.lancs.ac.uk Language: English - Date: 2011-01-27 19:30:30 Statistical classification Data mining Support vector machine Anomaly detection Document classification Unsupervised learning Kernel methods Supervised learning Margin classifier Statistics Machine learning Artificial intelligence
340	30 IP1 Exploring the Power of Heterogeneous Information Networks in Data Mining Multiple typed objects in the real world are interconnected, forming complex heterogeneous information networks. Diﬀerent from some studi Add to Reading List Source URL: www.siam.org Language: English - Date: 2011-04-21 13:49:43 Data analysis Data mining Networks Consensus clustering Community structure Graph theory Link analysis Anomaly detection Biclustering Statistics Cluster analysis Machine learning

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