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WWW
2009
ACM
14 years 3 months ago
A general framework for adaptive and online detection of web attacks
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detectio...
Wei Wang 0012, Florent Masseglia, Thomas Guyet, Re...
HIS
2004
13 years 10 months ago
Adaptive Boosting with Leader based Learners for Classification of Large Handwritten Data
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
LCN
2007
IEEE
14 years 3 months ago
Search Algorithms for Unstructured Peer-to-Peer Networks
Abstract—We study the performance of several search algorithms on unstructured peer-to-peer networks, both using classic search algorithms such as flooding and random walk, as w...
Reza Dorrigiv, Alejandro López-Ortiz, Pawel...
PRIB
2009
Springer
135views Bioinformatics» more  PRIB 2009»
14 years 3 months ago
Sequential Hierarchical Pattern Clustering
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
Bassam Farran, Amirthalingam Ramanan, Mahesan Nira...
RAID
2007
Springer
14 years 3 months ago
The NIDS Cluster: Scalable, Stateful Network Intrusion Detection on Commodity Hardware
Abstract. In this work we present a NIDS cluster as a scalable solution for realizing high-performance, stateful network intrusion detection on commodity hardware. The design addre...
Matthias Vallentin, Robin Sommer, Jason Lee, Craig...