English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

As the most competitive solution for next-generation network,software-defined network (SDN) and its dominant implementation OpenFlow, areattracting more and more interests. But besides convenience and flexibility,SDN/OpenFlow also introduces new kinds of limitations and security issues. Ofthese limitations, the most obvious and maybe the most neglected one, is theflow table capacity of SDN/OpenFlow switches.  In this paper, we proposed a novel inference attack targeting at SDN/OpenFlownetwork, which is motivated by the limited flow table capacities ofSDN/OpenFlow switches and the following measurable network performance decreaseresulting from frequent interactions between data plane and control plane whenthe flow table is full. To our best knowledge, this is the first proposedinference attack model of this kind for SDN/OpenFlow. We also implemented aninference attack framework according to our model and examined its efficiencyand accuracy. The simulation results demonstrate that our framework can inferthe network parameters(flow table capacity and flow table usage) with anaccuracy of 80% or higher. These findings give us a deeper understanding ofSDN/OpenFlow limitations and serve as guidelines to future improvements ofSDN/OpenFlow.

An Inference Attack Model for Flow Table Capacity and Usage: Exploiting the Vulnerability of Flow Table Overflow in Software-Defined Network