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» Intrusion Detection Based on Data Mining
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ICDM
2007
IEEE
199views Data Mining» more  ICDM 2007»
15 years 6 months ago
Discovering Structural Anomalies in Graph-Based Data
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
CIA
2008
Springer
15 years 1 months ago
Trust-Based Classifier Combination for Network Anomaly Detection
Abstract. We present a method that improves the results of network intrusion detection by integration of several anomaly detection algorithms through trust and reputation models. O...
Martin Rehák, Michal Pechoucek, Martin Gril...
IDEAL
2005
Springer
15 years 5 months ago
Identification of Anomalous SNMP Situations Using a Cooperative Connectionist Exploratory Projection Pursuit Model
Abstract. The work presented in this paper shows the capability of a connectionist model, based on a statistical technique called Exploratory Projection Pursuit (EPP), to identify ...
Álvaro Herrero, Emilio Corchado, José...
JAIR
2010
181views more  JAIR 2010»
14 years 6 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
ACSAC
2003
IEEE
15 years 3 months ago
Bayesian Event Classification for Intrusion Detection
Intrusion detection systems (IDSs) attempt to identify attacks by comparing collected data to predefined signatures known to be malicious (misuse-based IDSs) or to a model of lega...
Christopher Krügel, Darren Mutz, William K. R...