Targeted and anonymized smartphone-based public health interventions in a participatory sensing system

Public health interventions comprising information dissemination to affect behavioral adjustment have long been a significant component of public health campaigns. However, there has been limited development of public health intervention systems to make use of advances in mobile computing and telecommunications technologies. Such developments pose significant challenges to privacy and security where potentially sensitive data may be collected. In our previous work we identified and demonstrated the feasibility of using mobile devices as anonymous public health data collection devices as part of a Health Participatory Sensing Network (HPSN). An advanced capability of these networks extended in this paper would be the ability to distribute, apply, report on and analyze the usage and effectiveness of targeted public health interventions in an anonymous way. In this paper we describe such a platform, its place in the HPSN and demonstrate its feasibility through an implementation.

[1]  John P. Rula,et al.  Crowd (soft) control: moving beyond the opportunistic , 2012, HotMobile '12.

[2]  Gianluca Demartini,et al.  NoizCrowd: A Crowd-Based Data Gathering and Management System for Noise Level Data , 2013, MobiWIS.

[3]  Erik P. de Vink,et al.  A Formalization of Anonymity and Onion Routing , 2004, ESORICS.

[4]  Tim Furche,et al.  Spatial k-Anonymity , 2009, Encyclopedia of Database Systems.

[5]  Robert Steele,et al.  A Smartphone-Based System for Population-Scale Anonymized Public Health Data Collection and Intervention , 2014, 2014 47th Hawaii International Conference on System Sciences.

[6]  Radha Poovendran,et al.  A Survey on Mix Networks and Their Secure Applications , 2006, Proceedings of the IEEE.

[7]  Minho Shin,et al.  Anonysense: privacy-aware people-centric sensing , 2008, MobiSys '08.

[9]  Robert Steele,et al.  Summarized data to achieve population-wide anonymized wellness measures , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  Robert Steele,et al.  Health participatory sensing networks , 2014, Mob. Inf. Syst..

[11]  Mani B. Srivastava,et al.  SensorSafe: A Framework for Privacy-Preserving Management of Personal Sensory Information , 2011, Secure Data Management.

[12]  Robert Steele,et al.  Personal health record architectures: Technology infrastructure implications and dependencies , 2012, J. Assoc. Inf. Sci. Technol..

[13]  Deborah Estrin,et al.  Personal data vaults: a locus of control for personal data streams , 2010, CoNEXT.

[14]  Karl Aberer,et al.  ExposureSense: Integrating daily activities with air quality using mobile participatory sensing , 2013, 2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[15]  Delphine Christin Impenetrable obscurity vs. informed decisions: privacy solutions for Participatory Sensing , 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).