Understanding People’s Preferences for Disclosing Contextual Information to Smartphone Apps
Smartphones have become the primary and most intimate computing devices that people rely on for their daily tasks. Sensor-based and network technologies have turned smartphones into a “context-aware” information hub and a vehicle for information exchange. These information provide apps and third party with a wealth of sensitive information to mine and profile user behavior. However, the Orwellian implications created by context-awareness technology have caused uneasiness to people when using smartphone applications and reluctance of using them . To mitigate people’s privacy concerns, previous research suggests giving controls to people on how their information should be collected, accessed and shared. However, deciding who (people or the application) gets to access to what (types of information) could be an unattainable task. In order to develop appropriate applications and privacy policies it is important to understand under what circumstances people are willing to disclose information.
KeywordsDeveloper Type Grocery Store Information Disclosure Decision Tree Algorithm Data Requestor
Unable to display preview. Download preview PDF.
- 2.Barkhuus, L.: The mismeasurement of privacy: using contextual integrity to reconsider privacy in hci. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2012, pp. 367–376. ACM (2012)Google Scholar
- 4.Castañeda, J., Montoro, F.: The effect of Internet general privacy concern on customer behavior. Electronic Commerce Research (2007)Google Scholar
- 5.Consolvo, S., Smith, I.E., Matthews, T., LaMarca, A., Tabert, J., Powledge, P.: Location disclosure to social relations: why, when, & what people want to share. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2005, pp. 81–90. ACM (2005)Google Scholar
- 6.Madden, M., Boyles, J.L., Smith, A.: Privacy and data management on mobile devices. Technical Report CS-2011-02, Pew Research Center (September 2012)Google Scholar
- 7.Jedrzejczyk, L., Mancini, C., Corapi, D., Price, B., Bandara, A., Nuseibeh, B.: Learning from context: A field study of privacy awareness system for mobile devices (2011)Google Scholar
- 8.Kahneman, D., Krueger, A., Schkade, D., Schwarz, N., Stone, A.: A Survey Method for Characterizing Daily Life Experience: The Day Reconstruction Method (2004)Google Scholar
- 9.Khalil, A., Connelly, K.: Context-aware telephony: privacy preferences and sharing patterns. In: Proceedings of the 2006 20th Anniversary Conference on Computer Supported Cooperative Work, CSCW 2006, pp. 469–478. ACM (2006)Google Scholar
- 10.Larson, R., Csikszentmihalyi, M.: The experience sampling method. New Directions for Methodology of Social and Behavioral Science 15, 41–56 (1983)Google Scholar
- 11.Mancini, C., Thomas, K., Rogers, Y., Price, B., Jedrzejczyk, L., Bandara, A., Joinson, A., Nuseibeh, B.: From spaces to places: emerging contexts in mobile privacy. In: Proceedings of the 11th International Conference on Ubiquitous Computing, pp. 1–10 (2009)Google Scholar
- 12.Patil, S., Lai, J.: Who gets to know what when: configuring privacy permissions in an awareness application. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI 2005, pp. 101–110. ACM (2005)Google Scholar
- 13.Westin, A., Harris, L. Associates: Equifax-Harris Consumer Privacy Survey. Equifax (1996)Google Scholar