A Markov game privacy preserving model in retail applications

New retail applications induce integration of many components as NFC (Near Field Communication), M2M (Machine-To-Machine), IoT (Internet of Things), Web applications, etc. in large business sectors, such as payment services, products manufacturing, supply chain management, etc. Sensors, integrated in everyday products may facilitate threats as users tracking and profiling. An increasing concern about privacy threats posed by data affluence and device ubiquity takes place. This paper presents a privacy scheme for retail applications, discusses challenges related to customer profiling, client consent, device and information security. To protect customers' data, we propose a Markovian game, with detailed states, actions, strategies and transitions available for data holder to reach a compromise between privacy concessions and incentive motivation proposed by data requester. Numerical results are used to analyze and evaluate the game theory-based model.