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

Xiaoyu Li, Osamu Yoshie, Daoping Huang

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトル18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 - Proceedings
出版社Association for Computing Machinery
ページ335-339
ページ数5
Part F126325
ISBN(電子版)9781450348072
DOI
出版ステータスPublished - 2016 11 28
イベント18th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2016 - Singapore, Singapore
継続期間: 2016 11 282016 11 30

Other

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

ASJC Scopus subject areas

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

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