NFV-driven intrusion detection for smart manufacturing

被引：3

作者：

Behnke, Daniel ^{[1
]}

Mueller, Marcel ^{[1
]}

Boek, Patrick-Benjamin ^{[1
]}

Schneider, Stefan ^{[2
]}

Peuster, Manuel ^{[2
]}

Karl, Holger ^{[2
]}

Rocha, Alberto ^{[3
]}

Mesquita, Miguel ^{[3
]}

Bonnet, Jose ^{[3
]}

机构：

[1] Weidmuller Grp, Detmold, Germany

[2] Paderborn Univ, Paderborn, Germany

[3] Altice Labs, Aveiro, Portugal

来源：

2019 IEEE CONFERENCE ON NETWORK FUNCTION VIRTUALIZATION AND SOFTWARE DEFINED NETWORKS (IEEE NFV-SDN) | 2019年

基金：

欧盟地平线“2020”;

关键词：

FUTURE;

D O I：

10.1109/nfv-sdn47374.2019.9039956

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The significant progress in softwarization of hardware components with technologies like Network Function Virtualization (NFV) enables manifold applications for the industry, especially for smart manufacturing. The gained agility and flexibility leverages data gathering and analysis. In this work, we focus on a very important precondition for networked manufacturing: cyber security. We provide concepts and a first proof-ofwork for an cloud-native NFV-driven Intrusion Detection System using Kubernetes, stating challenges we solved during the process and the used software tools. Focusing on traffic monitoring and filtering to enable certain guidelines to ensure the integrity of the factory network by an automatic reconfiguration of the Network Services.

引用

页数：6

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