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TJS
2010
182views more  TJS 2010»
15 years 5 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
203
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CNSR
2005
IEEE
112views Communications» more  CNSR 2005»
16 years 1 months ago
Generating Representative Traffic for Intrusion Detection System Benchmarking
In this paper, a modeling and simulation framework is proposed for generating data for training and testing intrusion detection systems. The framework can develop models of web us...
Hilmi Günes Kayacik, A. Nur Zincir-Heywood
ICONIP
2004
15 years 8 months ago
Hybrid Feature Selection for Modeling Intrusion Detection Systems
Most of the current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (...
Srilatha Chebrolu, Ajith Abraham, Johnson P. Thoma...
JNCA
2007
179views more  JNCA 2007»
15 years 7 months ago
Modeling intrusion detection system using hybrid intelligent systems
The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known as intrusion detection system (IDS). This paper p...
Sandhya Peddabachigari, Ajith Abraham, Crina Grosa...
208
Voted
TSP
2008
101views more  TSP 2008»
15 years 7 months ago
Optimal Node Density for Detection in Energy-Constrained Random Networks
The problem of optimal node density maximizing the Neyman-Pearson detection error exponent subject to a constraint on average (per node) energy consumption is analyzed. The spatial...
Animashree Anandkumar, Lang Tong, Ananthram Swami