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A Weighted Risk Score Model for IoT Devices

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11637))

Abstract

The Internet of Things (IoT) defines a new era where ordinary physical objects are being transformed into smart connected devices. These advanced devices have the ability to sense, compute, and communicate with their surroundings via the Internet. This may result in severe network security breaches, as these devices in-crease the attack surface by exposing new vulnerabilities and infiltration points into restricted networks. One of the major challenges in such deployments is determining the security risks that IoT devices pose to the environment they operated in. This paper proposes an IoT device risk score model, denoted as the Weighted Risk Ranking (WRR) model. The proposed approach focuses on quantifying the static and dynamic properties of a device, in order to define a risk score. Our practical proof of concept demonstrates the use of the WRR scheme for several IoT devices in the context of an enterprise network, showing the feasibility of the suggested solution as a tool for device risk assessment in modern networks where IoT devices are widely deployed.

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Correspondence to Shachar Siboni .

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Siboni, S., Glezer, C., Shabtai, A., Elovici, Y. (2019). A Weighted Risk Score Model for IoT Devices. In: Wang, G., Feng, J., Bhuiyan, M., Lu, R. (eds) Security, Privacy, and Anonymity in Computation, Communication, and Storage. SpaCCS 2019. Lecture Notes in Computer Science(), vol 11637. Springer, Cham. https://doi.org/10.1007/978-3-030-24900-7_2

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  • DOI: https://doi.org/10.1007/978-3-030-24900-7_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24899-4

  • Online ISBN: 978-3-030-24900-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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