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NIPS
2004
15 years 3 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
147
Voted
DSOM
2007
Springer
15 years 8 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...
147
Voted
DDECS
2006
IEEE
146views Hardware» more  DDECS 2006»
15 years 6 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...
146
Voted
MM
2010
ACM
196views Multimedia» more  MM 2010»
15 years 2 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
15 years 2 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,...