Towards statistical trust computation for medical smartphone networks based on behavioral profiling

Weizhi Meng, Man Ho Allen Au

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)


Due to the popularity of mobile devices, medical smartphone networks (MSNs) have been evolved, which become an emerging network architecture in healthcare domain to improve the quality of service. There is no debate among security experts that the security of Internet-enabled medical devices is woefully inadequate. Although MSNs are mostly internally used, they still can leak sensitive information under insider attacks. In this case, there is a need to evaluate a node’s trustworthiness in MSNs based on the network characteristics. In this paper, we focus on MSNs and propose a statistical trust-based intrusion detection mechanism to detect malicious nodes in terms of behavioral profiling (e.g., camera usage, visited websites, etc.). Experimental results indicate that our proposed mechanism is feasible and promising in detecting malicious nodes under medical environments.
Original languageEnglish
Title of host publicationTrust Management XI - 11th IFIP WG 11.11 International Conference, IFIPTM 2017, Proceedings
PublisherSpringer New York LLC
Number of pages8
ISBN (Print)9783319591704
Publication statusPublished - 1 Jan 2017
Event11th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2017 - Gothenburg, Sweden
Duration: 12 Jun 201716 Jun 2017

Publication series

NameIFIP Advances in Information and Communication Technology
ISSN (Print)1868-4238


Conference11th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2017


  • Emerging network
  • Insider attack
  • Intrusion Detection
  • Medical smartphone network
  • Statistical trust computation

ASJC Scopus subject areas

  • Information Systems and Management

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