An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Sensors

Sandeep Pirbhulal¹  Heye Zhang¹  Subhas Chandra Mukhopadhyay³  Chunyue Li¹  Yumei Wang²  Guanglin Li¹  Wanqing Wu¹  Yuan-Ting Zhang¹ 

[1] Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China; E-Mails:;Shenzhen Nanshan District Xili Hospital, Shenzhen 518055, China; E-Mail:;School of Engineering and Advanced Technology, Massey University, Palmerston North 4442, New Zealand; E-Mail:

关键词: Body Sensor Network (BSN);    biometric;    efficiency;    Electrocardiogram (ECG);    Heart Rate Variability (HRV);    security;   

DOI  :  10.3390/s150715067

来源: mdpi

【 摘 要 】

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.