We address the problem of bootstrapping security and privacy policies for newly-deployed apps in wireless body area networks (WBAN) composed of smartphones, sensors and other wearable devices. We introduce a framework to model such a WBAN as an undirected graph whose vertices correspond to devices, apps and app resources, while edges model structural relationships among them. This graph is then augmented with attributes capturing the features of each entity together with user-defined tags. We then adapt available graph-based similarity metrics to find the closest app to a new one to be deployed, with the aim of reusing, and possibly adapting, its security policy. We illustrate our approach through a detailed smartphone ecosystem case study. Our results suggest that the scheme can provide users with a reasonably good policy that is consistent with the user’s security preferences implicitly captured by policies already in place.
['Ana Isabel González-Tablas', 'Juan E. Tapiador']
Bootstrapping Security Policies for Wearable Apps Using Attributed Structural Graphs