Quantum Game Analysis of Privacy-Leakage for Application Ecosystems

Personalized applications often provide their functionality by extracting sensitive data from users. Such a strategy brings potential threats to users' privacy because malicious applications may sell users' sensitive data to third-parties for economic interests. The state-of-the-art literature addresses the privacy issue mainly from a technical perspective. In this paper, we take a different angle in which the main players involving privacy leakage are studied from a connected perspective rather than an isolated one. More specifically, we propose the concept of application ecosystem, which consists of user, application, and adversary (malicious third-party) as entities. Our aim is to analyze the tension forces inside the application ecosystem and their impacts on the behavior of each player, which can serve as a theoretical basis for designing effective and efficient privacy preservation solutions from a management level. Another outstanding trait of our analysis is the adoption of quantum game theory to model the application ecosystem, which is suitable because the important property of entanglement in quantum games can be employed to well depict the inner tension forces among the user, application, and adversary. This makes us take an important step towards understanding the complexity of decision-making from rational individuals. To the best of our knowledge, we are the first to quantize the privacy leakage issue. The simulation results quantitatively demonstrate how the mutual restrictions among all players determine their strategies and hence the development of the application ecosystem.