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FTCS
1993
111views more  FTCS 1993»
13 years 11 months ago
Detection and Discrimination of Injected Network Faults
Although the present work does in fact employ training data, it does so in the interest of calibrating the results Six hundred faults were induced by injection into five live obtai...
Roy A. Maxion, Robert T. Olszewski
JAIR
2010
181views more  JAIR 2010»
13 years 4 months ago
Intrusion Detection using Continuous Time Bayesian Networks
Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems (NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor sys...
Jing Xu, Christian R. Shelton
FLAIRS
2010
14 years 11 days ago
Using a Graph-Based Approach for Discovering Cybercrime
The ability to mine data represented as a graph has become important in several domains for detecting various structural patterns. One important area of data mining is anomaly det...
William Eberle, Lawrence B. Holder, Jeffrey Graves
IEEEARES
2006
IEEE
14 years 4 months ago
Identifying Intrusions in Computer Networks with Principal Component Analysis
Most current anomaly Intrusion Detection Systems (IDSs) detect computer network behavior as normal or abnormal but cannot identify the type of attacks. Moreover, most current intr...
Wei Wang, Roberto Battiti
ICDM
2010
IEEE
216views Data Mining» more  ICDM 2010»
13 years 8 months ago
Data Editing Techniques to Allow the Application of Distance-Based Outlier Detection to Streams
The problem of finding outliers in data has broad applications in areas as diverse as data cleaning, fraud detection, network monitoring, invasive species monitoring, etc. While th...
Vit Niennattrakul, Eamonn J. Keogh, Chotirat Ann R...