Sciweavers

CVPR
2010
IEEE
13 years 4 months ago
Anomaly detection in crowded scenes
A novel framework for anomaly detection in crowded scenes is presented. Three properties are identified as important for the design of a localized video representation suitable f...
Vijay Mahadevan, Weixin Li, Viral Bhalodia, Nuno V...
MM
2010
ACM
196views Multimedia» more  MM 2010»
13 years 4 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
GECCO
2008
Springer
152views Optimization» more  GECCO 2008»
13 years 5 months ago
Combatting financial fraud: a coevolutionary anomaly detection approach
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
Shelly Xiaonan Wu, Wolfgang Banzhaf
ANLP
2000
92views more  ANLP 2000»
13 years 6 months ago
Detecting Errors within a Corpus using Anomaly Detection
We present a method for automatically detecting errors in a manually marked corpus using anomaly detection. Anomaly detection is a method for determining which elements of a large...
Eleazar Eskin
NIPS
2004
13 years 6 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
ICISC
2004
169views Cryptology» more  ICISC 2004»
13 years 6 months ago
ADWICE - Anomaly Detection with Real-Time Incremental Clustering
Abstract. Anomaly detection, detection of deviations from what is considered normal, is an important complement to misuse detection based on attack signatures. Anomaly detection in...
Kalle Burbeck, Simin Nadjm-Tehrani
DMIN
2006
152views Data Mining» more  DMIN 2006»
13 years 6 months ago
Anomaly Detection Using the Dempster-Shafer Method
In this paper, we implement an anomaly detection system using the Dempster-Shafer method. Using two standard benchmark problems we show that by combining multiple signals it is pos...
Qi Chen, Uwe Aickelin
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 6 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi
ECBS
2007
IEEE
188views Hardware» more  ECBS 2007»
13 years 6 months ago
Behavior Analysis-Based Learning Framework for Host Level Intrusion Detection
Machine learning has great utility within the context of network intrusion detection systems. In this paper, a behavior analysis-based learning framework for host level network in...
Haiyan Qiao, Jianfeng Peng, Chuan Feng, Jerzy W. R...
CIA
2008
Springer
13 years 6 months ago
Trust-Based Classifier Combination for Network Anomaly Detection
Abstract. We present a method that improves the results of network intrusion detection by integration of several anomaly detection algorithms through trust and reputation models. O...
Martin Rehák, Michal Pechoucek, Martin Gril...