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» Anomaly Detection Using Visualization and Machine Learning
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CCS
2009
ACM
15 years 4 months ago
Active learning for network intrusion detection
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf...
IMC
2009
ACM
15 years 4 months ago
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
Statistical machine learning techniques have recently garnered increased popularity as a means to improve network design and security. For intrusion detection, such methods build ...
Benjamin I. P. Rubinstein, Blaine Nelson, Ling Hua...
SDM
2009
SIAM
202views Data Mining» more  SDM 2009»
15 years 7 months ago
Proximity-Based Anomaly Detection Using Sparse Structure Learning.
We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data a...
Tsuyoshi Idé, Aurelie C. Lozano, Naoki Abe,...
JNCA
2007
136views more  JNCA 2007»
14 years 9 months ago
Adaptive anomaly detection with evolving connectionist systems
Anomaly detection holds great potential for detecting previously unknown attacks. In order to be effective in a practical environment, anomaly detection systems have to be capable...
Yihua Liao, V. Rao Vemuri, Alejandro Pasos
TR
2010
204views Hardware» more  TR 2010»
14 years 4 months ago
Anomaly Detection Through a Bayesian Support Vector Machine
This paper investigates the use of a one-class support vector machine algorithm to detect the onset of system anomalies, and trend output classification probabilities, as a way to ...
Vasilis A. Sotiris, Peter W. Tse, Michael Pecht