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NIPS
2004
13 years 8 months ago
Density Level Detection is Classification
We show that anomaly detection can be interpreted as a binary classification problem. Using this interpretation we propose a support vector machine (SVM) for anomaly detection. We...
Ingo Steinwart, Don R. Hush, Clint Scovel
DSOM
2007
Springer
14 years 1 months ago
NADA - Network Anomaly Detection Algorithm
This paper deals with a new iterative Network Anomaly Detection Algorithm – NADA, which accomplishes the detection, classification and identification of traffic anomalies. NADA f...
Silvia Farraposo, Philippe Owezarski, Edmundo Mont...
DDECS
2006
IEEE
146views Hardware» more  DDECS 2006»
13 years 11 months ago
Automatic Identification of Timing Anomalies for Cycle-Accurate Worst-Case Execution Time Analysis
Abstract-- Hard real-time systems need methods to determine upper bounds for their execution times, usually called worst-case execution times. Timing anomalies are counterintuitive...
Jochen Eisinger, Ilia Polian, Bernd Becker, Alexan...
MM
2010
ACM
196views Multimedia» more  MM 2010»
13 years 7 months ago
Non-parametric anomaly detection exploiting space-time features
In this paper a real-time anomaly detection system for video streams is proposed. Spatio-temporal features are exploited to capture scene dynamic statistics together with appearan...
Lorenzo Seidenari, Marco Bertini
SIGCOMM
2010
ACM
13 years 7 months ago
Automating root-cause analysis of network anomalies using frequent itemset mining
Finding the root-cause of a network security anomaly is essential for network operators. In our recent work [1, 5], we introduced a generic technique that uses frequent itemset mi...
Ignasi Paredes-Oliva, Xenofontas A. Dimitropoulos,...