Body Area Network (BAN) is one of the most important techniques for observing patient health in real time and identifying and analyzing diseases. For effective implementation of this technology in practice and to benefit from it, there are some key issues which are to be addressed, and among those issues, security is highly critical. WBAN will have to operate in a cooperative networking model of multiple networks such as those of homogeneous networks, for the purpose of performance and reliability, or those of heterogeneous networks, for the purpose of data transfer and processing from application point of view, with the other networks such as the networks of hospitals, clinics, medical experts, etc. and the patient himself/herself, who may be moving from one network to another. This paper brings out the issues related to security in WBAN in separate networks as well as in multiple networks. For WBAN working in a separate network, the IEEE 802.15.6 standard is considered. For WBANs working in multiple networks, especially heterogeneous networks, the security issues are considered. Considering the advancements of artificial intelligence (AI), the paper describes how AI is addressing some challenges faced by WBAN. The paper describes possible approaches which can be taken to address these issues by modeling a security mechanism using various artificial intelligence techniques. The paper proposes game theory with Stackelberg security equilibrium (GTSSE) for modeling security in heterogeneous networks in WBAN and describes the experiments conducted by the authors and the results proving the suitability of the modeling using GTSSE.
Keywords: Body Area Network (BAN); eHealthcare; game theory; heterogeneous networking; network security.