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Content Provider | IEEE Xplore Digital Library |
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Author | Yanyan Li Mengjun Xie Jiang Bian |
Copyright Year | 2014 |
Description | Author affiliation: Univ. of Arkansas for Med. Sci., Little Rock, AR, USA (Jiang Bian) || Univ. of Arkansas at Little Rock, Little Rock, AR, USA (Yanyan Li; Mengjun Xie) |
Abstract | Electronic consent becomes increasingly popular in the healthcare sector given the many benefits it provides. However, security concerns, e.g., how to verify the identity of a person who is remotely accessing the electronic consent system in a secure and user-friendly manner, also arise along with the popularity of electronic consent. Unfortunately, existing electronic consent systems do not pay sufficient attention to those issues. They mainly rely on conventional password based authentication to verify the identity of an electronic consent user, which is far from being sufficient given that identity theft threat is real and significant in reality. In this paper, we present a security enhanced electronic consent model called USign. USign enhances the identity protection and authentication for electronic consent systems by leveraging handwritten signatures everyone is familiar with and mobile computing technologies that are becoming ubiquitous. We developed a prototype of USign and conducted preliminary evaluation on accuracy and usability of signature verification. Our experimental results show the feasibility of the proposed model. |
Sponsorship | IEEE Eng. Med. Biol. Soc. |
Starting Page | 4487 |
Ending Page | 4490 |
File Size | 728709 |
Page Count | 4 |
File Format | |
ISBN | 9781424479290 |
ISSN | 1557170X |
DOI | 10.1109/EMBC.2014.6944620 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-08-26 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Authentication Usability Prototypes Forgery Accuracy |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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