Artificial Immune Systems and Fuzzy Logic to Detect Flooding Attacks in Software-Defined Networks

Identifier Binding Attacks and Defenses in Software-Defined Networks

In this work, we demonstrate a novel attack in SDN networks, Persona Hijacking, that breaks the bindings of all layers of the networking stack and fools the network infrastructure into believing that the attacker is the legitimate owner of the victim’s identifiers, which significantly increases persistence. We then present a defense, SECUREBINDER, that prevents identifier binding attacks at all...

Logic Programming for Software-Defined Networks

SPHINX: Detecting Security Attacks in Software-Defined Networks

Software-defined networks (SDNs) allow greater control over network entities by centralizing the control plane, but place great burden on the administrator to manually ensure security and correct functioning of the entire network. We list several attacks on SDN controllers that violate network topology and data plane forwarding, and can be mounted by compromised network entities, such as end ho...

Early Detection of DDoS Attacks in Software Defined Networks Controller

Training Artificial Neural Networks for Fuzzy Logic

P roblems requiring inferencing with Boolean logic have been implemented in percept rons or feedforward networks, and some attempts have been made to implement fuzzy logic based inferencing in similar networks. In this pap er, we present producti ve networks , which are art ificial neur al networks, meant for fuzzy logic based inferencing. The nod es in t hese networks collect an offset product...