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» Anomaly Detection Using Visualization and Machine Learning
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TJS
2010
182views more  TJS 2010»
14 years 8 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
KDD
1998
ACM
181views Data Mining» more  KDD 1998»
15 years 2 months ago
Approaches to Online Learning and Concept Drift for User Identification in Computer Security
The task in the computer security domain of anomaly detection is to characterize the behaviors of a computer user (the `valid', or `normal' user) so that unusual occurre...
Terran Lane, Carla E. Brodley
ICML
2001
IEEE
15 years 10 months ago
Bayesian approaches to failure prediction for disk drives
Hard disk drive failures are rare but are often costly. The ability to predict failures is important to consumers, drive manufacturers, and computer system manufacturers alike. In...
Greg Hamerly, Charles Elkan
FI
2010
130views more  FI 2010»
14 years 7 months ago
Improving Anomaly Detection for Text-Based Protocols by Exploiting Message Structures
: Service platforms using text-based protocols need to be protected against attacks. Machine-learning algorithms with pattern matching can be used to detect even previously unknown...
Martin Güthle, Jochen Kögel, Stefan Wahl...
ITCC
2005
IEEE
15 years 3 months ago
Application of Loop Reduction to Learning Program Behaviors for Anomaly Detection
Abstract: Evidence of some attacks can be manifested by abnormal sequences of system calls of programs. Most approaches that have been developed so far mainly concentrate on some p...
Jidong Long, Daniel G. Schwartz, Sara Stoecklin, M...