Towards Statistical Trust Computation for Medical Smartphone Networks Based on Behavioral Profiling - Trust Management XI Access content directly
Conference Papers Year : 2017

Towards Statistical Trust Computation for Medical Smartphone Networks Based on Behavioral Profiling

Abstract

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.
Fichier principal
Vignette du fichier
450659_1_En_12_Chapter.pdf (230.09 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01651152 , version 1 (28-11-2017)

Licence

Attribution

Identifiers

Cite

Weizhi Meng, Man Ho Au. Towards Statistical Trust Computation for Medical Smartphone Networks Based on Behavioral Profiling. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. pp.152-159, ⟨10.1007/978-3-319-59171-1_12⟩. ⟨hal-01651152⟩
71 View
70 Download

Altmetric

Share

Gmail Facebook X LinkedIn More