Energy efficient cluster formation and secure data outsourcing using TEOSCC and ECDH-IBT technique in WBAN

WBAN is a network of miniature biomedical sensors centered as implantable, wearable and around the human body to measure various physiological parameters in real time. Due to a resource-constrained nature of WBAN, a number of challenges have emerged. The prominent being the energy efficiency issue, which has been tackled in our work. Our research work concentrates on two operations i.e. clustering and encryption. Clustering is a widely used method to improve energy efficiency. The proposed algorithm is a static energy efficient clustering algorithm TEOSCC, which partitions the WBAN into static-time generated clusters. Clustering is accomplished by taking into consideration the spatial distribution of body sensor nodes, path loss during transmission, the transmission energy and a threshold value, making the scheme energy efficient. Including to TEOSCC another proposed approach is a novel ECDH-IBT algorithm, an energy efficient asymmetric block encryption scheme based on ECDH key exchange, which uses one way XOR function to protect the security/privacy and maintain good energy efficiency for WBAN's. Using generator points of an elliptic curve, the public-private key pair was generated and was used for encryption between the body sensor node and the base station, relieving the need of additional encryption on the cluster-head. Particularity of ECDH-IBT is that it can provide a reasonable security even with smaller key size.