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Summary: Distributed Learning Mechanism Against
Flooding Network Attacks
Josep L. Berral1
, Javier Alonso2
, Nicolas Poggi1
, Ricard Gavald`a3
, Manish Parashar4
and
Jordi Torres2
Abstract-- Adaptive techniques based on machine
learning and data mining are gaining relevance in self-
management and self-defense for networks and dis-
tributed systems. In this paper, we focus on early
detection and stopping of distributed flooding attacks
and network abuses. We extend the framework pro-
posed by Zhang and Parashar (2006) to cooperatively
detect and react to abnormal behaviors before the tar-
get machine collapses and network performance de-
grades. In this framework, nodes in an intermediate
network share information about their local traffic ob-
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