Document Type
Article
Language
eng
Publication Date
7-2017
Publisher
Elsevier
Source Publication
Future Generation Computer Systems
Source ISSN
0167-739X
Abstract
RFID (Radio Frequency IDentification) is anticipated to be a core technology that will be used in many practical applications of our life in near future. It has received considerable attention within the healthcare for almost a decade now. The technology’s promise to efficiently track hospital supplies, medical equipment, medications and patients is an attractive proposition to the healthcare industry. However, the prospect of wide spread use of RFID tags in the healthcare area has also triggered discussions regarding privacy, particularly because RFID data in transit may easily be intercepted and can be send to track its user (owner). In a nutshell, this technology has not really seen its true potential in healthcare industry since privacy concerns raised by the tag bearers are not properly addressed by existing identification techniques. There are two major types of privacy preservation techniques that are required in an RFID based healthcare system—(1) a privacy preserving authentication protocol is required while sensing RFID tags for different identification and monitoring purposes, and (2) a privacy preserving access control mechanism is required to restrict unauthorized access of private information while providing healthcare services using the tag ID. In this paper, we propose a framework (PriSens-HSAC) that makes an effort to address the above mentioned two privacy issues. To the best of our knowledge, it is the first framework to provide increased privacy in RFID based healthcare systems, using RFID authentication along with access control technique.
Recommended Citation
Rahman, Farzana; Bhuiyan, Anwarul A.; and Ahamed, Sheikh Iqbal, "A Privacy Preserving Framework for RFID Based Healthcare Systems" (2017). Mathematics, Statistics and Computer Science Faculty Research and Publications. 614.
https://epublications.marquette.edu/mscs_fac/614
Comments
Accepted version. Future Generation Computer Systems, Vol. 72 (July 2017): 339-352. DOI. © 2017 Elsevier B.V. Used with permission.