An IoT-Based Anonymous Function for Security and Privacy in Healthcare Sensor Networks

Xiao Chun Yin, Zeng Guang Liu, Bruce Ndibanje, Lewis Nkenyereye, S. M.Riazul Islam

Research output: Contribution to journalArticlepeer-review

33 Citations (Scopus)

Abstract

In the age of the Internet of Things, connected devices are changing the delivery system in the healthcare communication environment. With the integration of IoT in healthcare, there is a huge potential for improvement of the quality, safety, and effciency of health care in addition to promising technological, economical, and social prospects. Nevertheless, this integration comes with security risks such as data breach that might be caused by credential-stealing malware. In addition, the patient valuable data can be disclosed when the perspective devices are compromised since they are connected to the internet. Hence, security has become an essential part of today’s computing world regarding the ubiquitous nature of the IoT entities in general and IoT-based healthcare in particular. In this paper, research on the algorithm for anonymizing sensitive information about health data set exchanged in the IoT environment using a wireless communication system has been presented. To preserve the security and privacy, during the data session from the users interacting online, the algorithm defines records that cannot be revealed by providing protection to user’s privacy. Moreover, the proposed algorithm includes a secure encryption process that enables health data anonymity. Furthermore, we have provided an analysis using mathematical functions to valid the algorithm’s anonymity function. The results show that the anonymization algorithm guarantees safety features for the considered IoT system applied in context of the healthcare communication systems.
Original languageEnglish
Article number3146
Number of pages14
JournalSensors (Switzerland)
Volume19
Issue number14
DOIs
Publication statusPublished - 17 Jul 2019
Externally publishedYes

Fingerprint

Dive into the research topics of 'An IoT-Based Anonymous Function for Security and Privacy in Healthcare Sensor Networks'. Together they form a unique fingerprint.

Cite this