Joint optimization of the physical layer security with end-to-end delay management is studied in the uniquely constrained context of wireless body area networks (WBANs). A game-theoretic framework is proposed wherein body-worn sensor devices interact in the presence of wiretappers and under fading channel conditions to find the most secure multi-hop path to the hub, while adhering to the end-to-end delay requirements imposed by the application. We model the problem as the search for a Nash network topology where no unilateral deviation in strategy by any single sensor node improves the secrecy of its transmissions, and provide a distributed algorithm guaranteed to converge to a Pareto-dominant Nash solution. The framework is evaluated through numerical simulations in conditions approximating actual deployment of WBANs for moving and stationary scenarios. Results validate the merits of the proposed framework to improve the security of transmissions compared with the star topology and IEEE 802.15.6 two-hop topology extension with a best-channel algorithm, at the expense of an admissible increase in the end-to-end delay.

A game-theoretic approach is proposed to investigate the problem of relay selection and power control with quality of service constraints in multiple-access wireless body area networks (WBANs). Each sensor node seeks a strategy that ensures the optimal energy efficiency and, at the same time, provides a guaranteed upper bound on the end-to-end packet delay and jitter. The existence of Nash equilibrium for the proposed non-cooperative game is proved, the Nash power control solution is analytically calculated, and a distributed algorithm is provided that converges to a Nash relay selection solution. The game theoretic analysis is then employed in an IEEE 802.15.6-based WBAN to gauge the validity and effectiveness of the proposed framework. Performance behaviors in terms of energy efficiency and end-to-end delay and jitter are examined for various scenarios. Results demonstrate the merits of the proposed framework, particularly for moving WBANs under severe fading conditions.

A robust optimization model is considered for nonzero-sum discounted stochastic games with incomplete information in order to formally formulate and analyze the intrusion detection problem in wireless sensor networks (WSNs). Security requirements of WSNs are taken into account to characterize the game parameters and model the player objectives. To generalize the problem, the game data are assumed not to be fully known to the players, who take a robust optimization approach to address this data uncertainty. For assessing the validity and effectiveness of the framework, illustrative instances of the developed game model are generated. Equilibrium analysis reveals how the conflicting objectives of the intruder and intrusion detection system compel them to adopt different conservative stances toward data uncertainty. It is also shown, by numerical results, that the robust approach in the presence of uncertainty reduces the sensitivity of the solution with respect to data perturbations, and thus improves design stability.