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» Intrusion Detection using Continuous Time Bayesian Networks
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FPL
2005
Springer
119views Hardware» more  FPL 2005»
14 years 1 months ago
Real-Time Feature Extraction for High Speed Networks
With the onset of Gigabit networks, current generation networking components will soon be insufficient for numerous reasons: most notably because existing methods cannot support h...
David Nguyen, Gokhan Memik, Seda Ogrenci Memik, Al...
UAI
2004
13 years 9 months ago
Bayesian Biosurveillance of Disease Outbreaks
Early, reliable detection of disease outbreaks is a critical problem today. This paper reports an investigation of the use of causal Bayesian networks to model spatio-temporal pat...
Gregory F. Cooper, Denver Dash, John Levander, Wen...
CONEXT
2007
ACM
13 years 9 months ago
Detecting worm variants using machine learning
Network intrusion detection systems typically detect worms by examining packet or flow logs for known signatures. Not only does this approach mean worms cannot be detected until ...
Oliver Sharma, Mark Girolami, Joseph S. Sventek
AUSAI
2006
Springer
13 years 11 months ago
Modular Bayesian Networks for Inferring Landmarks on Mobile Daily Life
Abstract. Mobile devices get to handle much information thanks to the convergence of diverse functionalities. Their environment has great potential of supporting customized service...
Keum-Sung Hwang, Sung-Bae Cho
ICASSP
2009
IEEE
14 years 2 months ago
A Bayesian NETWORKS approach for dialog modeling: The fusion BN
Bayesian Networks, BNs, are suitable for mixed-initiative dialog modeling allowing a more flexible and natural spoken interaction. This solution can be applied to identify the in...
Fernando F. Fernández-Martínez, Javi...