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» Online Anomaly Detection under Adversarial Impact
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JMLR
2010
198views more  JMLR 2010»
13 years 2 months ago
Online Anomaly Detection under Adversarial Impact
Security analysis of learning algorithms is gaining increasing importance, especially since they have become target of deliberate obstruction in certain applications. Some securit...
Marius Kloft, Pavel Laskov
CCS
2009
ACM
14 years 2 months ago
A framework for quantitative security analysis of machine learning
We propose a framework for quantitative security analysis of machine learning methods. Key issus of this framework are a formal specification of the deployed learning model and a...
Pavel Laskov, Marius Kloft
DSN
2008
IEEE
14 years 2 months ago
Anomaly? application change? or workload change? towards automated detection of application performance anomaly and change
: Automated tools for understanding application behavior and its changes during the application life-cycle are essential for many performance analysis and debugging tasks. Applicat...
Ludmila Cherkasova, Kivanc M. Ozonat, Ningfang Mi,...
IFIPTM
2010
113views Management» more  IFIPTM 2010»
13 years 6 months ago
Impact of Trust Management and Information Sharing to Adversarial Cost in Ranking Systems
Ranking systems such as those in product review sites and recommender systems usually use ratings to rank favorite items based on both their quality and popularity. Since higher ra...
Le-Hung Vu, Thanasis G. Papaioannou, Karl Aberer
ISBI
2008
IEEE
14 years 8 months ago
Distributed online anomaly detection in high-content screening
This paper presents an automated, online approach to anomaly detection in high-content screening assays for pharmaceutical research. Online detection of anomalies is attractive be...
Adam Goode, Rahul Sukthankar, Lily B. Mummert, Mei...