e-mission / e-mission-upc-aggregator

BSD 3-Clause "New" or "Revised" License
0 stars 2 forks source link

Related work #19

Open shankari opened 4 years ago

shankari commented 4 years ago

Here, we will list related, commercially available projects and how they are different from UPC. So far, we have:

Key differentiators:

njriasan commented 4 years ago

Here are some additional similarities I see:

Password managers/password vaults:

Personal Data Stores (Solid, Hub of All Things, OpenPDS):

Personal Clouds (Cozy Cloud, NextCloud, MyCloud, Freedom Box):

Platforms as a Service (Heroku, Google App Engine):

If This Then That:

shankari commented 4 years ago

Stuart Macmillan pointed me to https://flip.it/qP_HNR which labels itself as "GitHub for Data".

My take on it is that it was primarily focused on publishing synthetic data, similar to prior work on publishing cellphone location data -e.g.

Mir, Darakhshan J., Sibren Isaacman, Ramon Caceres, Margaret Martonosi, and Rebecca N. Wright. 2013. “DP-WHERE: Differentially Private Modeling of Human Mobility.” In 2013 IEEE International Conference on Big Data, 580–88. Silicon Valley, CA, USA: IEEE. https://doi.org/10.1109/BigData.2013.6691626.

Jack looked into that for his MS thesis, and what we found was that in order to get the DP privacy budget right, the data is typically really coarse. This is fine-ish if you are talking about cellular data, which is already coarse to begin with, but not that great if you want to explore street-level data from fine-grained GPS traces.

They also still assume that the datasets are controlled by developers at big organizations, instead of users controlling their own data.

shankari commented 4 years ago

How about enigma? https://enigma.co/

They published a cryptographic solution for contact tracing https://blog.enigma.co/safetrace-privacy-preserving-contact-tracing-for-covid-19-c5ae8e1afa93

shankari commented 4 years ago

Also, for the record, openmined (https://www.openmined.org/) does DP learning. Note directly related but good to put into related work.