Privacy Through Choice - BSidesLondon 2014

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This document discusses a startup called Privacy Through Choice that aims to review the security and privacy of web services. It will provide simple reports for end users and more detailed reports for technologists. The startup is currently in the early stages with limited resources and is seeking help from volunteers in areas like coding, testing, documentation and moderation. It aims to eventually transition to a community-driven model where moderation is replaced by a reputation system.

Technology

TYPICAL
USER?family
friends
Home
businesse
s

< A> I'm kinda confused. I'm not very good at this...
:)
< B> are people going to be paying for this service
or are you just playing with a personal project?
< A> It's real application with paying yes
< B> can I suggest that you have someone else work on
the security?
< B> no offense
< A> None taken! That would be awesome but we're a
startup with limited resources.

• Review security and privacy of web services
• Independent
• Community-driven
• Open source
PRIVACY
THROUGH CHOICE
@ptc_org

• Using publicly available information (not a pen test)
• Simple reports for end users
• Detailed reports for technologists and decision makers
• Encourages best practices
• Encourages transparency from service providers
PRIVACY
THROUGH CHOICE
@ptc_org

ROADMAP
• Getting started – Available to everyone but
with fixed moderators
• Community-driven – Fixed moderation
replaced by system of reputation and merit
• Social – Optional enhanced usability such as
following sites, users etc.
• ??? – Driven by feedback
@ptc_org

YOU CAN HELP
• Rails coders (or a rewrite)
• Front end developers & graphics
• Code review
• Pen tests
• Automation & IaC
• Documentation
• Sites and moderators
Community
@ptc_org

WANT TO HELP?
• http://privacythroughchoice.org/bsides
• http://bit.ly/ptc_org
• @ptc_org
• @zeroXten (me)
• Find me
@ptc_org

My work brings me in contact with the cutting edge in science research and the developments in public policy. I find one common thread when interacting with people in these fields. The question of how can we make more use of large public data while ensuring privacy of the individuals involved. Large amounts of specific types of data can be useful to both scientists and policy makers in myriad ways. But currently there exists no policy framework one could use to take the public in confidence and simultaneously leverage data without conflict of interest. This problem is an underrated one. Steps taken towards such a policy initiative can be one of the defining intellectual exercise of the 21st century reaping huge benefits for science and policy spheres. And eventually these benefits can be put to used for many purposes. The building of this framework needs grounded knowledge of data science, computer science and public policy to make sure it is robust in every sense. I am an engineer who has built machine learning systems at scale and now I am transitioning into a data journalism and policy career. My past and current experience gives me a unique vantage point to look at this problem. It would be a honour to express myself at Data_Science Conference.

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