MeDI: Measurement-based Device Identification Framework for Internet of Things

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

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129 Downloads (Pure)

Abstract

IoT systems may provide information from different sensors that may reveal potentially confidential data, such as a person's presence or not. The primary question to address is how we can identify the sensors and other devices in a reliable way before receiving data from them and using or sharing it. In other words, we need to verify the identity of sensors and devices. A malicious device could claim that it is the legitimate sensor and trigger security problems. For instance, it might send false data about the environment, harmfully affecting the outputs and behavior of the system. For this purpose, using only primary identity values such as IP address, MAC address, and even the public-key cryptography key pair is not enough since IPs can be dynamic, MACs can be spoofed, and cryptography key pairs can be stolen. Therefore, the server requires supplementary security considerations such as contextual features to verify the device identity. This paper presents a measurement-based method to detect and alert false data reports during the reception process by means of sensor behavior. As a proof of concept, we develop a classification-based methodology for device identification, which can be implemented in a real IoT scenario.
Original languageEnglish
Title of host publicationProceedings - IEEE 16th International Conference on Industrial Informatics, INDIN 2018
PublisherIEEE
Pages95-100
Number of pages6
ISBN (Electronic)978-1-5386-4829-2
ISBN (Print)978-1-5386-4830-8
DOIs
Publication statusPublished - 27 Sep 2018
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Industrial Informatics - University of Porto's Engineering Faculty (FEUP), Porto, Portugal
Duration: 18 Jul 201820 Jul 2018
Conference number: 16
https://web.fe.up.pt/~indin2018/
https://web.fe.up.pt/~indin2018/

Conference

ConferenceIEEE International Conference on Industrial Informatics
Abbreviated titleINDIN
CountryPortugal
CityPorto
Period18/07/201820/07/2018
Internet address

Keywords

  • Internet of Things
  • device identification
  • device profiling
  • identity theft
  • smart campus

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