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Intrusion Prevention System Evaluation for SDN-Enabled IoT Systems

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Abstract

As the importance of communication networks increases in our lives, the limitations of traditional networks start to emerge. Software Defined Networking (SDN) is the most recent paradigm in the networking industry, its purpose being to mitigate traditional network limitations, such as complexity, the difficulty of introducing new services in the network, the inability of enforcing security policies while having a network-wide view. From a security point of view, the need for middleboxes in the network, such as firewalls or Intrusion Detection/Prevention Systems (IDS/IPS) is eliminated by implementing these functionalities in software applications. As SDN has the potential of becoming a key enabler for the Internet of Things (IoT), there are specific aspects of security for IoT that need to be taken into account, for example the lack of powerful computing resources or limited battery life, making securing IoT devices more challenging. This paper addresses one of these security issues, while evaluating a simple IPS application for an SDN controller. An emulated IoT network is controlled by the SDN controller, which also runs an IPS application. When a node becomes faulty or it is compromised and it sends too much traffic, that could cause a Denial of Service (DoS) in the network, it is blocked by the controller for a configurable amount of time.

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Acknowledgments

This work has been funded by University Politehnica of Bucharest, through the “Excellence Research Grants” Program, UPB – GEX. Identifier: UPB–EXCELENTA–2016 project “Platform for Studying Security in IoT”, contract number 96/2016 (PaSS-IoT), by UEFISCDI Romania under grants no. 20/2012 “Scalable Radio Transceiver for Instrumental Wireless Sensor Networks - SaRaT-IWSN” and 262EU/2014 eWALL support project and by the European Commission by FP7 IP project no. 610658/2013 “eWALL for Active Long Living - eWALL”.

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Correspondence to Alexandru Vulpe .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Stancu, A., Arseni, SC., Vulpe, A., Fratu, O., Halunga, S. (2018). Intrusion Prevention System Evaluation for SDN-Enabled IoT Systems. In: Oliver, N., Serino, S., Matic, A., Cipresso, P., Filipovic, N., Gavrilovska, L. (eds) Pervasive Computing Paradigms for Mental Health. FABULOUS MindCare IIOT 2016 2016 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-319-74935-8_21

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  • DOI: https://doi.org/10.1007/978-3-319-74935-8_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74934-1

  • Online ISBN: 978-3-319-74935-8

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