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» Intrusion Detection using Continuous Time Bayesian Networks
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JMLR
2010
137views more  JMLR 2010»
13 years 2 months ago
Importance Sampling for Continuous Time Bayesian Networks
A continuous time Bayesian network (CTBN) uses a structured representation to describe a dynamic system with a finite number of states which evolves in continuous time. Exact infe...
Yu Fan, Jing Xu, Christian R. Shelton
ISSA
2004
13 years 8 months ago
Utilizing Neural Networks For Effective Intrusion Detection
Computer security, and intrusion detection in particular, has become increasingly important in today's business environment, to help ensure safe and trusted commerce between ...
Martin Botha
JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
WOWMOM
2005
ACM
201views Multimedia» more  WOWMOM 2005»
14 years 1 months ago
Real-Time Intrusion Detection for Ad Hoc Networks
A mobile ad hoc network is a collection of nodes that is connected through a wireless medium forming rapidly changing topologies. The widely accepted existing routing protocols de...
Ioanna Stamouli, Patroklos G. Argyroudis, Hitesh T...
ICEIS
2008
IEEE
14 years 1 months ago
Next-Generation Misuse and Anomaly Prevention System
Abstract. Network Intrusion Detection Systems (NIDS) aim at preventing network attacks and unauthorised remote use of computers. More accurately, depending on the kind of attack it...
Pablo Garcia Bringas, Yoseba K. Penya