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.
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Jan-Philipp Steghöfer; Babak Esfandiari. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-505, pp.152-159, 2017, Trust Management XI. 〈10.1007/978-3-319-59171-1_12〉
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Weizhi Meng, Man Au. Towards Statistical Trust Computation for Medical Smartphone Networks Based on Behavioral Profiling. Jan-Philipp Steghöfer; Babak Esfandiari. 11th IFIP International Conference on Trust Management (TM), Jun 2017, Gothenburg, Sweden. Springer International Publishing, IFIP Advances in Information and Communication Technology, AICT-505, pp.152-159, 2017, Trust Management XI. 〈10.1007/978-3-319-59171-1_12〉. 〈hal-01651152〉

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