Publication Details

Survey of Privacy Enabling Strategies in IoT Networks

HELLEBRANDT, L.; HUJŇÁK, O.; HANÁČEK, P.; HOMOLIAK, I. Survey of Privacy Enabling Strategies in IoT Networks. In Proceedings of the 2017 International Conference on Computer Science and Artificial Intelligence. Jakarta: Association for Computing Machinery, 2017. p. 216-221. ISBN: 978-1-4503-5392-2.
Czech title
Přehled strategií pro zachování soukromí v IoT sítích
Type
conference paper
Language
English
Authors
URL
Keywords

Privacy; Anonymity; IoT; Internet of Things; LoRa; ZigBee

Abstract

In this paper, we discuss privacy issues in modern networks for Internet of Things. We focus on anonymization of both devices and users in the context of both IP and non-IP networks. We take a closer look on two current non-IP technologies - LoRaWan and ZigBee. Those represent two distinct groups of Internet of Things (IoT) networks - Low Power WANs covering large areas and providing connectivity as a service, and Wireless PANs following traditional scheme with a local network interconnecting IoT devices. For both IP and non-IP networks we analyze possible approaches to preserve privacy of connected devices and identify open problems for future investigation. We propose strategies for ensuring privacy for IoT devices in IP, LPWAN and PAN networks based on their specific features and analyze possible problems of suggested strategies.

Published
2017
Pages
216–221
Proceedings
Proceedings of the 2017 International Conference on Computer Science and Artificial Intelligence
ISBN
978-1-4503-5392-2
Publisher
Association for Computing Machinery
Place
Jakarta
DOI
UT WoS
000455681900040
EID Scopus
BibTeX
@inproceedings{BUT146271,
  author="Lukáš {Hellebrandt} and Ondřej {Hujňák} and Petr {Hanáček} and Ivan {Homoliak}",
  title="Survey of Privacy Enabling Strategies in IoT Networks",
  booktitle="Proceedings of the 2017 International Conference on Computer Science and Artificial Intelligence",
  year="2017",
  pages="216--221",
  publisher="Association for Computing Machinery",
  address="Jakarta",
  doi="10.1145/3168390.3168440",
  isbn="978-1-4503-5392-2",
  url="https://dl.acm.org/citation.cfm?id=3168440"
}
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