Paper Info
Title
Cognitive security management with reputation based cooperation schemes in heterogeneous networks
Abstract
This paper proposes a computational intelligence framework for network security management. The framework uses reinforcement learning and Bayesian methods to achieve cross-layer optimization in heterogeneous, multi-layer wireless and wireline networks. Metrics based on the reputation of a node are used to measure performance. OPNET simulations results indicate that routing algorithms based on the newly proposed framework exhibit nearly four times improved network performance measured in terms of goodput.
Year
DOI
Venue
2009
10.1109/CICYBS.2009.4925085
CICS
Keywords
Field
DocType
reputation based cooperation schemes,computational intelligence framework,belief networks,reinforcement learning,multilayer wireless networks,learning (artificial intelligence),multilayer wireline networks,cognitive security management,radio networks,telecommunication computing,cross-layer optimization,telecommunication network management,bayesian methods,routing algorithms,telecommunication security,telecommunication network routing,wireless communication,learning artificial intelligence,security management,routing,network performance,heterogeneous network,wireless sensor networks,network security,computational intelligence,estimation,bayesian method
Cross-layer optimization,Computational intelligence,Computer science,Computer network,Goodput,Heterogeneous network,Wireless sensor network,Network performance,Distributed computing,Security management,Reinforcement learning
Conference
ISBN
Citations 
PageRank 
978-1-4244-2769-7
2
0.37
References 
Authors
7
7
Name
Order
Citations
PageRank
Minsoo Lee131531.33
Xiaohui Ye2836.65
Samuel Johnson361.13
Dan Marconett4402.70
Vadrevu S. K. Chaitanya520.37
Rao Vemuri6143.12
S. J. Ben Yoo717224.55