A passive means based privacy protection method for the perceptual layer of IoTs

Xiaoyu Li, Osamu Yoshie, Daoping Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Privacy protection in Internet of Things (IoTs) has long been the topic of extensive research in the last decade. The perceptual layer of IoTs suffers the most significant privacy disclosing because of the limitation of hardware resources. Data encryption and anonymization are the most common methods to protect private information for the perceptual layer of IoTs. However, these efforts are ineffective to avoid privacy disclosure if the communication environment exists unknown wireless nodes which could be malicious devices. Therefore, in this paper we derive an innovative and passive method called Horizontal Hierarchy Slicing (HHS) method to detect the existence of unknown wireless devices which could result negative means to the privacy. PAM algorithm is used to cluster the HHS curves and analyze whether unknown wireless devices exist in the communicating environment. Link Quality Indicator data are utilized as the network parameters in this paper. The simulation results show their effectiveness in privacy protection.

Original languageEnglish
Title of host publication18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 - Proceedings
PublisherAssociation for Computing Machinery
Pages335-339
Number of pages5
VolumePart F126325
ISBN (Electronic)9781450348072
DOIs
Publication statusPublished - 2016 Nov 28
Event18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 - Singapore, Singapore
Duration: 2016 Nov 282016 Nov 30

Other

Other18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016
CountrySingapore
CitySingapore
Period16/11/2816/11/30

Keywords

  • Horizontal Hierarchy Slicing
  • Internet of Things
  • Link Quality Indicator
  • Privacy protection

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Fingerprint Dive into the research topics of 'A passive means based privacy protection method for the perceptual layer of IoTs'. Together they form a unique fingerprint.

  • Cite this

    Li, X., Yoshie, O., & Huang, D. (2016). A passive means based privacy protection method for the perceptual layer of IoTs. In 18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 - Proceedings (Vol. Part F126325, pp. 335-339). Association for Computing Machinery. https://doi.org/10.1145/3011141.3011153