Security Ranking of IoT Devices Using an AHP Model

Shachar Siboni, Chanan Glezer, Rami Puzis, Asaf Shabtai, Yuval Elovici

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

The proliferation of Internet of Things (IoT) technology raises major security and privacy concerns. Specifically, ordinary electrical appliances are being transformed into smart connected devices with the capability to sense, compute, and communicate with their surroundings and the Internet. These smart embedded devices increase the attack surface of the environments in which they are deployed by becoming new points of entry for malicious activities, resulting in severe network security flaws. One of the major challenges lies in examining the influence of IoT devices on the security level of the environment they operate within. In this paper, we propose a security ranking model for IoT devices, based on the analytic hierarchy process (AHP) technique, which can be used for the device risk assessment task. Our implementation of the AHP model is based on a device-centric approach, where both device-specific features and domain-related features are taken into account. We applied the proposed model on several IoT devices in the context of an enterprise network environment, demonstrating its feasibility in analyzing security-related considerations in smart environments.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - 4th International Symposium, CSCML 2020, Proceedings
EditorsShlomi Dolev, Gera Weiss, Vladimir Kolesnikov, Sachin Lodha
PublisherSpringer
Pages29-44
Number of pages16
ISBN (Print)9783030497842
DOIs
StatePublished - 1 Jan 2020
Event4th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020 - Beersheba, Israel
Duration: 2 Jul 20203 Jul 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12161 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2020
Country/TerritoryIsrael
CityBeersheba
Period2/07/203/07/20

Keywords

  • Analytic hierarchy process
  • Device ranking
  • Internet of Things
  • Risk assessment
  • Security

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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