Privacy/Roadmap/2014: Difference between revisions

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== Goal: Firefox users know when they are being tracked ==
== Goal: Firefox users know when they are being tracked ==
* (Research, implementation) Use machine learning to classify tracking domains, similar to EFF’s Privacy Badger (light on info) and UW’s TrackingObserver (github, NSDI paper).
* (Research, implementation) Use machine learning to classify tracking domains, similar to EFF’s Privacy Badger (light on info) and UW’s TrackingObserver (github, NSDI paper).
  * Status: Mostly research oriented right now, none of these have been productionized or used at scale.
** Status: Mostly research oriented right now, none of these have been productionized or used at scale.
  * Roadblocks:
      * (Research) None of these have been run on a large enough data sets to determine realistic false positive and false negative rates for users in the wild.
      * (Policy) Per-user classification is not very interesting -- to take advantage of the Firefox user-base we’d want willing participants to share their data in order to improve global identification of tracking domains for everyone. Any feature that relies on user-input for correction or aggregation (such as the “Report Spam” feature in webmail) will require Mozilla to collect user data. Historically this has been challenging for us.
      * (Implementation) Feasibility is not clear. Avoiding false positives (domains incorrectly identified as tracking) is much more important than avoiding false negatives (tracking domains not identified), but both are important for effectiveness and good UX. This requires running a service. Historically we don’t have a good track record on this kind of problem.

Revision as of 23:50, 25 March 2014

DRAFT Privacy Roadmap for 2014

Background

In 2013, the public discussion around privacy focussed heavily on the wholesale collection of data and metadata from browsing and cell phone usage. Tracking has entered the public consciousness thanks to the Verizon revelations, Edward Snowden’s whistleblowing on the NSA, multi-national government involvement in surveillance, and news coverage on ad-tech companies monetizing browsing histories through tracking.


For the purposes of this document, tracking is any technique that can be used to accumulate history (browsing, messaging, purchase) and associate it with a particular person. Major sources of tracking include:

  • Deliberate tracking for delivering targeted ads
  • Social network widgets (“Like” button, +1 button, Retweet, etc.) and other services whose primary goal may not be tracking, but could be used for tracking

Non-goals for 2014 Non-tracking privacy related efforts. We currently don’t have headcount to tackle more than tracking efforts in 2014, although non-tracking potential goals are listed at the end. We should focus on a single area to strengthen our user story, increase likelihood of making progress, and concentrate impact.


This roadmap doesn’t discuss SSL-everywhere, which is already included on the security roadmap. How we work This list is cribbed from the SecurityEngineering wiki, plus Policy.

Goal: Firefox users know when they are being tracked

  • (Research, implementation) Use machine learning to classify tracking domains, similar to EFF’s Privacy Badger (light on info) and UW’s TrackingObserver (github, NSDI paper).
    • Status: Mostly research oriented right now, none of these have been productionized or used at scale.