Privacy preservation using game theory in e-health application

Arbia Riahi Sfar (1) , Enrico Natalizio (2, 3) , Sahbi Mazlout (1) , Yacine Challal (4) , Zied Chtourou (1)

1 Military Academy of Tunisia
2 TII - Technology Innovation Institute
3 SIMBIOT - SIMulating and Building IOT
4 LMCS - Laboratoire de Méthodes de Conception de Systèmes

In the domain of the new e-health applications, the ubiquitous nature of intelligent devices raises legitimate questions about the privacy of persons, and how to cope with the heterogeneity of user and application requirements in terms of security services. This requires the development of adaptive, context-aware and user-centric security solutions. Recent e-health applications (M2M/IoT/Web) permit remote monitoring of patient health, medical treatments, fitness information and parameters, alarm triggering, etc. Since the monitored device is tightly related to a human being, new changes arise regarding communications facilities constraints, private data protection, trust relationships, etc. In this work, we propose a Markovian game between data holder and data requester, in a weight loss program, to protect data privacy. We aim to reach a compromise between privacy concessions made by data holder and incentive motivation proposed by data requester. Finally, we show numerical results of executed experiments to evaluate the proposed model.

Mots clés: Internet of things; e-health; game theory; Markovian process; Privacy

Domaines: Informatique et théorie des jeux [cs.GT]

Arbia Riahi Sfar, Enrico Natalizio, Sahbi Mazlout, Yacine Challal, Zied Chtourou. Privacy preservation using game theory in e-health application. Journal of information security and applications, 2022, 66, pp.103158. ⟨10.1016/j.jisa.2022.103158⟩. ⟨hal-03620373⟩