Privacy is Essential to a Trustworthy Internet: the Case of Divvi Up

RESEARCH QUESTION 

Divvi Up is a system developed to provide privacy-respecting metrics for COVID-19 exposure notification apps. This research focuses on discovering, designing, building, and testing to determine what is required in order to deliver Internet-scale privacy benefits across a wide range of use cases, with ease of use and accessibility as core attributes. The research question is: How can we enforce the promises made in a privacy policy through technology that is ubiquitous and affordable? 

The specific research questions are: (1) How do we make Divvi Up affordable for app owners with limited financial resources but substantial metric-gathering security/privacy implications? (2) How do we ensure the Divvi Up Application Programming Interface (API) has a user-friendly functionality (i.e. an easy to navigate Divvi Up website/dashboard)? (3) How do we ensure Divvi Up will work effectively in a wide variety of situations/contexts? (4) What metrics/computations are future Divvi Up users likely to find valuable? and (5) What standardizations still need to be established so the system will function at an Internet scale? 

WHY IS THIS RESEARCH IMPORTANT? 

Applications generate valuable metrics about their users that are the basis for insights into users’ behaviour. Users must trust that application owners will respect their stated privacy and security policies. Stated policies, however, are insufficient as privacy safeguards. Once an app owner has user data, privacy policies can be violated, and the mere possibility of privacy violations can erode trust in applications, making users less likely to want to engage. Moving metrics collection to more privacy-respecting systems would be transformational for peoples’ privacy because of the sheer amount of data that applications collect. By ensuring privacy, trust in the Internet and applications that rely upon the Web can be built. 

This research is applied at an Internet-wide scale to realign application privacy practices with what people expect, making the trust they put in applications well-placed instead of reliant on simple promises made in a privacy policy. The research contains properties that will be beneficial to securing privacy not only on the Internet but also valuable in repressive and otherwise difficult operating environments. 

The research seeks to serve the public around the world, not just those organizations who can afford to adopt the technology. By answering the research questions, an Internet that is more secure and privacy-respecting can be built, one that is more trustworthy than it is today. 

METHODOLOGY  

The research gathers and analyzes data by testing the Divvi Up system in its own experimental implementation and in collaboration with Cloudflare, Mozilla, and others. In addition to test implementations, the research gathers and analyzes input through collaboration with the Internet Engineering Task Force (IETF) community, which is open to the public. Finally, in a collaborative environment, a set of questions are asked about what app owners and users need from the Divvi Up system and to members of the open-source community to gather feedback and input. 

*Please note that the image in this summary is for illustrative purposes only and does not depict the described project.

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