Security Blog
The latest news and insights from Google on security and safety on the Internet
Learning statistics with privacy, aided by the flip of a coin
October 30, 2014
Cross-posted on the
Research Blog
and the
Chromium Blog
At Google, we are constantly trying to improve the techniques we use to
protect our users' security and privacy
. One such project, RAPPOR (Randomized Aggregatable Privacy-Preserving Ordinal Response), provides a new state-of-the-art, privacy-preserving way to learn software statistics that we can use to better safeguard our users’ security, find bugs, and improve the overall user experience.
Building on the concept of
randomized response
, RAPPOR enables learning statistics about the behavior of users’ software while guaranteeing client privacy. The guarantees of
differential privacy
, which are widely accepted as being the
strongest form of privacy
, have almost never been used in practice despite
intense research in academia
. RAPPOR introduces a practical method to achieve those guarantees.
To understand RAPPOR, consider the following example. Let’s say you wanted to count how many of your online friends were dogs, while respecting the maxim that,
on the Internet, nobody should know you’re a dog
. To do this, you could ask each friend to answer the question “Are you a dog?” in the following way. Each friend should flip a coin in secret, and answer the question truthfully if the coin came up heads; but, if the coin came up tails, that friend should always say “Yes” regardless. Then you could get a good estimate of the true count from the greater-than-half fraction of your friends that answered “Yes”. However, you still wouldn’t know which of your friends was a dog: each answer “Yes” would most likely be due to that friend’s coin flip coming up tails.
RAPPOR builds on the above concept, allowing software to send reports that are effectively indistinguishable from the results of random coin flips and are free of any unique identifiers. However, by aggregating the reports we can learn the common statistics that are shared by many users. We’re currently testing the use of RAPPOR in Chrome, to learn statistics about how
unwanted software
is
hijacking
users’ settings.
We believe that RAPPOR has the potential to be applied for a number of different purposes, so we're making it freely available for all to use. We'll continue development of RAPPOR as a standalone
open-source project
so that anybody can inspect test its reporting and analysis mechanisms, and help develop the technology. We’ve written up the technical details of RAPPOR in a
report
that will be published next week at the
ACM Conference on Computer and Communications Security
.
We’re encouraged by the
feedback
we’ve received so far from academics and other stakeholders, and we’re looking forward to additional comments from the community. We hope that everybody interested in preserving user privacy will review the technology and share their feedback at
rappor-discuss@googlegroups.com
.
Posted by Úlfar Erlingsson, Tech Lead Manager, Security Research
No comments :
Post a Comment
Labels
#sharethemicincyber
#supplychain #security #opensource
android
android security
android tr
app security
big data
biometrics
blackhat
C++
chrome
chrome enterprise
chrome security
connected devices
CTF
diversity
encryption
federated learning
fuzzing
Gboard
google play
google play protect
hacking
interoperability
iot security
kubernetes
linux kernel
memory safety
Open Source
pha family highlights
pixel
privacy
private compute core
Rowhammer
rust
Security
security rewards program
sigstore
spyware
supply chain
targeted spyware
tensor
Titan M2
VDP
vulnerabilities
workshop
Archive
2024
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2023
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2022
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2021
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2020
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2019
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2018
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2017
Dec
Nov
Oct
Sep
Jul
Jun
May
Apr
Mar
Feb
Jan
2016
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2015
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
Jan
2014
Dec
Nov
Oct
Sep
Aug
Jul
Jun
Apr
Mar
Feb
Jan
2013
Dec
Nov
Oct
Aug
Jun
May
Apr
Mar
Feb
Jan
2012
Dec
Sep
Aug
Jun
May
Apr
Mar
Feb
Jan
2011
Dec
Nov
Oct
Sep
Aug
Jul
Jun
May
Apr
Mar
Feb
2010
Nov
Oct
Sep
Aug
Jul
May
Apr
Mar
2009
Nov
Oct
Aug
Jul
Jun
Mar
2008
Dec
Nov
Oct
Aug
Jul
May
Feb
2007
Nov
Oct
Sep
Jul
Jun
May
Feed
Follow @google
Follow
Give us feedback in our
Product Forums
.
Follow
No comments :
Post a Comment