A novel biometric algorithm to body sensor networks

Abstract

In Body Sensor Networks (BSN) several sensor nodes are attached on, inside or around human body to monitor vital sign signals such as, Electrocardiogram (ECG), Electroencephalogram (EEG), Blood pressure etc. The information from each sensor node is very significant; therefore privacy and security is very important during data transmission in BSN. The conventional cryptographic approaches make use of cryptographic keys to achieve authentication, and use of these keys not only require high resource utilization and computation time, but also consume large amount of energy, power and memory in BSN. Therefore, it is necessary to develop power efficient and less computational complex authentication technique for BSN. In this paper we design a novel biometric algorithm which is based on biometric feature Electrocardiogram (ECG) and uses Data Authentication Function (DAF) for the security of BSN instead of utilizing traditional key generation procedure. Our proposed algorithm is compared with two cryptographic authentication techniques, Data Encryption Standard (DES) which is symmetric or private-key based encryption technique and RSA (Rivest Shamir Adleman) which is asymmetric or public-key based encryption scheme. Simulation is performed in MATLAB and results explain that our algorithm is efficient in terms of transmission time utilization and average remaining energy.