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TJS
2010
182views more  TJS 2010»
15 years 4 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
RAID
2009
Springer
16 years 21 days 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 ...
INFOCOM
2008
IEEE
16 years 17 days ago
Detecting Anomalies Using End-to-End Path Measurements
—In this paper, we propose new “low-overhead” network monitoring techniques to detect violations of path-level QoS guarantees like end-to-end delay, loss, etc. Unlike existin...
K. V. M. Naidu, Debmalya Panigrahi, Rajeev Rastogi
ISSTA
2010
ACM
15 years 10 months ago
Learning from 6, 000 projects: lightweight cross-project anomaly detection
Real production code contains lots of knowledge—on the domain, on the architecture, and on the environment. How can we leverage this knowledge in new projects? Using a novel lig...
Natalie Gruska, Andrzej Wasylkowski, Andreas Zelle...
USS
2004
15 years 7 months ago
On Gray-Box Program Tracking for Anomaly Detection
Many host-based anomaly detection systems monitor a process ostensibly running a known program by observing the system calls the process makes. Numerous improvements to the precis...
Debin Gao, Michael K. Reiter, Dawn Xiaodong Song