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CCR
2006
114views more  CCR 2006»
13 years 8 months ago
A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular m...
Nigel Williams, Sebastian Zander, Grenville J. Arm...
CORR
2012
Springer
210views Education» more  CORR 2012»
12 years 3 months ago
MAV Stabilization using Machine Learning and Onboard Sensors
In many situations, Miniature Aerial Vehicles (MAVs) are limited to using only on-board sensors for navigation. This limits the data available to algorithms used for stabilization...
Jason Yosinski, Cooper Bills
LCN
2005
IEEE
14 years 1 months ago
Automated Traffic Classification and Application Identification using Machine Learning
The dynamic classification and identification of network applications responsible for network traffic flows offers substantial benefits to a number of key areas in IP network engi...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...
DAGM
2008
Springer
13 years 9 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof
FORTE
2008
13 years 9 months ago
Detecting Communication Protocol Security Flaws by Formal Fuzz Testing and Machine Learning
Network-based fuzz testing has become an effective mechanism to ensure the security and reliability of communication protocol systems. However, fuzz testing is still conducted in a...
Guoqiang Shu, Yating Hsu, David Lee