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RAID
2009
Springer
14 years 2 months ago
Protecting a Moving Target: Addressing Web Application Concept Drift
Because of the ad hoc nature of web applications, intrusion detection systems that leverage machine learning techniques are particularly well-suited for protecting websites. The re...
Federico Maggi, William K. Robertson, Christopher ...
ACSAC
2004
IEEE
13 years 11 months ago
RACOON: Rapidly Generating User Command Data For Anomaly Detection From Customizable Templates
One of the biggest obstacles faced by user command based anomaly detection techniques is the paucity of data. Gathering command data is a slow process often spanning months or yea...
Ramkumar Chinchani, Aarthie Muthukrishnan, Madhusu...
GRID
2007
Springer
14 years 1 months ago
Log summarization and anomaly detection for troubleshooting distributed systems
— Today’s system monitoring tools are capable of detecting system failures such as host failures, OS errors, and network partitions in near-real time. Unfortunately, the same c...
Dan Gunter, Brian Tierney, Aaron Brown, D. Martin ...
ICDM
2005
IEEE
271views Data Mining» more  ICDM 2005»
14 years 1 months ago
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the r...
Eamonn J. Keogh, Jessica Lin, Ada Wai-Chee Fu
RTSS
1999
IEEE
13 years 12 months ago
Timing Anomalies in Dynamically Scheduled Microprocessors
Previous timing analysis methods have assumed that the worst-case instruction execution time necessarily corresponds to the worst-case behavior. We show that this assumption is wr...
Thomas Lundqvist, Per Stenström