An open framework for flexible plug-in privacy mechanisms in crowdsensing applications

Autor: Spyros Lalis, George Theodorakopoulos, Manos Katsomallos, Thanasis Papaioannou
Rok vydání: 2017
Předmět:
Zdroj: PerCom Workshops
DOI: 10.1109/percomw.2017.7917564
Popis: Preserving user privacy is crucial for the wide adoption of crowdsensing and participatory sensing applications that rely on personal devices. Currently, each application comes with its own hardwired and possibly undocumented privacy support (if any), while the horizontal protection mechanisms provided by operating and runtime systems operate at a low level that can significantly harm application utility, or even render an application useless. To achieve greater flexibility, we propose a framework that decouples the privacy mechanism from the application logic so that it can be developed by another, perhaps more trusted party, and which allows the dynamic binding of different privacy mechanisms to the same application running on the user's mobile device. We describe a proof-of-concept implementation of the proposed framework for Android, where privacy mechanisms are independently developed as separate plug-in components. Based on a simple but powerful API, it is possible to implement a wide range of standard privacy approaches, including collaborative schemes that involve data exchanges among multiple personal devices.
Databáze: OpenAIRE