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» Anomaly Detection Using Process Mining
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ICMLA
2010
13 years 5 months ago
Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets
Abstract--Clinical electroencephalography (EEG) is routinely used to monitor brain function in critically ill patients, and specific EEG waveforms are recognized by clinicians as s...
Drausin Wulsin, Justin Blanco, Ram Mani, Brian Lit...
ICDM
2010
IEEE
168views Data Mining» more  ICDM 2010»
13 years 5 months ago
Anomaly Detection Using an Ensemble of Feature Models
We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model ...
Keith Noto, Carla E. Brodley, Donna K. Slonim
EVOW
2009
Springer
13 years 11 months ago
Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networks
In this paper the node-level decision unit of a self-learning anomaly detection mechanism for office monitoring with wireless sensor nodes is presented. The node-level decision uni...
Markus Wälchli, Torsten Braun
ICDM
2006
IEEE
158views Data Mining» more  ICDM 2006»
14 years 1 months ago
Detection of Interdomain Routing Anomalies Based on Higher-Order Path Analysis
Internet routing dynamics have been extensively studied in the past few years. However, dynamics such as interdomain Border Gateway Protocol (BGP) behavior are still poorly unders...
Murat Can Ganiz, Sudhan Kanitkar, Mooi Choo Chuah,...
KDD
1998
ACM
181views Data Mining» more  KDD 1998»
13 years 11 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