TY - JOUR
T1 - Fuzzy vault-based biometric security method for tele-health monitoring systems
AU - Pirbhulal, Sandeep
AU - Shang, Peng
AU - Wu, Wanqing
AU - Sangaiah, Arun Kumar
AU - Samuel, Oluwarotimi Williams
AU - Li, Guanglin
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2018/10
Y1 - 2018/10
N2 - This study proposed an efficient fuzzy vault-based security method that adopts time-domain parameters extracted from physiological signals for tele-healthcare applications, including rehabilitation and stress management systems among others. One of the main challenges of the existing fuzzy vault-based approaches is that they depend on frequency-domain parameters of bio-signals to generate entities identifiers which require more processing time and energy consumption. Hence, we firstly designed a wearable platform for bio-signals collection, and later extracted time-domain features from the signals to generate efficient and distinctive identifiers for securing medical data in tele-healthcare applications. The statistical tests and hamming distances were applied to verify the performance of the generated identifiers regarding their uniqueness and randomness, respectively. This research work considered a total of 30 subjects data and the experimental results reveal that the proposed approach has better performance in WBSNs regarding processing time (0.168 ms) and energy consumption (1.423 mJ) than the traditional techniques.
AB - This study proposed an efficient fuzzy vault-based security method that adopts time-domain parameters extracted from physiological signals for tele-healthcare applications, including rehabilitation and stress management systems among others. One of the main challenges of the existing fuzzy vault-based approaches is that they depend on frequency-domain parameters of bio-signals to generate entities identifiers which require more processing time and energy consumption. Hence, we firstly designed a wearable platform for bio-signals collection, and later extracted time-domain features from the signals to generate efficient and distinctive identifiers for securing medical data in tele-healthcare applications. The statistical tests and hamming distances were applied to verify the performance of the generated identifiers regarding their uniqueness and randomness, respectively. This research work considered a total of 30 subjects data and the experimental results reveal that the proposed approach has better performance in WBSNs regarding processing time (0.168 ms) and energy consumption (1.423 mJ) than the traditional techniques.
KW - Biometric
KW - Entity recognition
KW - Fuzzy vault
KW - Medical applications
KW - Security
KW - Tele-health monitoring
UR - http://www.scopus.com/inward/record.url?scp=85052445179&partnerID=8YFLogxK
U2 - 10.1016/j.compeleceng.2018.08.004
DO - 10.1016/j.compeleceng.2018.08.004
M3 - 文章
AN - SCOPUS:85052445179
SN - 0045-7906
VL - 71
SP - 546
EP - 557
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
ER -
