Subject: [ietf-privacy] Privacy vs. Machine Learning (Forum in Dresden Sept 21/22)

From: Thorsten Strufe <[email-masked]>
Date: Tue, 21 Apr 2015 14:32:58 +0200

Hi everybody,

considering the improvements and ubiquity of machine learning
applications, and the impact they (may) have on the privacy of
individuals, we want to bring together people interested in either of
the two sides, here in Dresden on Sept 21/22 2015 ( http://www.prinf.eu ).
 
To ignite discussions, we see two (rather obvious) topics, that we think
are important and interesting:
1)  considering all the public personal data by all sorts of people, we
wonder how good */inference attacks/* can actually get, even on people
who don't publish (a lot of) information about themselves
  - directly related of course is the question, if we can find new
*/privacy metrics,/* and
- if there are ways to encounter such attacks, without diminishing the
utility for the users (too much). And

2) on a related note we want to further explore ideas towards
*/privacy-preserving recommenders/*.

We will organize this event as a "traditional" scientific workshop
soliciting submissions, which will be reviewed and subsequently
published, to make it easier for the academic audiences to convince
their funding entity of its importance ;-) - but we really mainly want
to engage in discussions, may be fostering some future collaborations,
as well.

I'm attaching the usual Call for Papers - and I hope, of course, that we
will receive some interesting submissions (to make the official part
interesting - so help in advertising is appreciated). We will accept
both novel scientific contributions, but also datasets and replication
studies. But most importantly, we hope to attract a broad audience of
interested participants from different professional backgrounds, to
facilitate great discussions!

Thanks a lot!

Ulf & Thorsten

-- 
Thorsten Strufe                   
TU Dresden                           https://dud.inf.tu-dresden.de/
CASED                                          http://www.cased.de/