Detecting Malicious Nodes in Medical Smartphone Networks Through Euclidean Distance-Based Behavioral Profiling

Weizhi Meng, Wenjuan Li, Yu Wang, Man Au

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Abstract

With the increasing digitization of the healthcare industry, a wide range of medical devices are Internet- and inter-connected. Mobile devices (e.g., smartphones) are one common facility used in the healthcare industry to improve the quality of service and experience for both patients and healthcare personnel. The underlying network architecture to support such devices is also referred to as medical smartphone networks (MSNs). Similar to other networks, MSNs also suffer from various attacks like insider attacks (e.g., leakage of sensitive patient information by a malicious insider). In this work, we focus on MSNs and design a trust-based intrusion detection approach through Euclidean distance-based behavioral profiling to detect malicious devices (or called nodes). In the evaluation, we collaborate with healthcare organizations and implement our approach in a real simulated MSN environment. Experimental results demonstrate that our approach is promising in effectively identifying malicious MSN nodes.
Original languageEnglish
Title of host publicationCyberspace Safety and Security
PublisherSpringer
Publication date2017
Pages163-175
ISBN (Print)9783319694719
DOIs
Publication statusPublished - 2017
Event9th International Symposium on Cyberspace Safety and Security - Xi'an Jiyuan International Hotel , Xi'an , China
Duration: 23 Oct 201725 Oct 2017

Conference

Conference9th International Symposium on Cyberspace Safety and Security
Location Xi'an Jiyuan International Hotel
CountryChina
City Xi'an
Period23/10/201725/10/2017
SeriesCyberspace Safety and Security
Volume10581

Keywords

  • Collaborative network
  • Intrusion detection
  • Medical Smartphone Network
  • Trust computation and management
  • Insider attack
  • Malicious node

Cite this

Meng, W., Li, W., Wang, Y., & Au, M. (2017). Detecting Malicious Nodes in Medical Smartphone Networks Through Euclidean Distance-Based Behavioral Profiling. In Cyberspace Safety and Security (pp. 163-175). Springer. Cyberspace Safety and Security, Vol.. 10581 https://doi.org/10.1007/978-3-319-69471-9_12