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Decision Tree Based IoT Attack Detection in Programmable Data Plane Using P4 Language

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Advanced Information Networking and Applications (AINA 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 450))

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Abstract

The Internet of Things (IoT) is a massively growing domain. With this the threats are also growing. Software Defined Networking (SDNs) is an emerging architecture which separates the control plane and the data plane of a network. It is being put to practice in networks around the world to mitigate issues. With growing heterogeneity in IoT protocols, it is cumbersome and costly to use SDNs. The Programming Protocol-independent Packet Processors (P4) is an open source, domain-specific programming language for network devices, specifying how data plane devices (switches, routers, NICs, filters, etc.) process packets. To overcome the challenges of IoT, P4 language is ideal as it provides flexibility for programming the data plane. We propose a light and fast approach to use decision tree to detect attacks from network traces and form small header fields to implement high accuracy attack detection in the programmable data plane using the P4 language.

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Authors and Affiliations

  1. Department of Computer Science and Information Systems, Birla Institute of Technology and Science Pilani, Pilani, India

    Rahul Poddar & Hari Babu

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  1. Rahul Poddar
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  2. Hari Babu
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Correspondence to Rahul Poddar .

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Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. University of Technology Sydney, Sydney, NSW, Australia

    Farookh Hussain

  3. Faculty of Bussiness Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Poddar, R., Babu, H. (2022). Decision Tree Based IoT Attack Detection in Programmable Data Plane Using P4 Language. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 450. Springer, Cham. https://doi.org/10.1007/978-3-030-99587-4_57

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