Things that come to my mind:
*range blocks become impossible, and its impossible to tell if vandals are
using near by ips
*cant do a whois on the ip to see if its a library or something

Suppose those first two come down to the drawback of not knowing the ip is
you dont know the ip

More importantly, as details of the mapping become public, its hard to hide
them again. IPv4 addresses are usually dynamic, eventually some people will
publish what their hash is and ip, and then everyone knows the hash (and if
you follow a specific user you may be able to link one hash to another hash
as belonging to the same isp, and slowly puzzle things together. I imagine
data mining algorithms could be effective here, especially if you have edit
history from before and after the switch) this could result in a false
sense of security. Often in privacy situations less security is better than
false security

If people are looking into it, they probably know better than i do

--bawolff
On Apr 5, 2015 7:34 AM, "Cristian Consonni" <[email protected]> wrote:
>
> Hi,
>
> You may have followed the discussion on Wikimedia-l (and enwiki-l).
>
> For a mere intellectual curiosity I would like to know why hashing the IPs
> with a varying salt won't work.
>
> Wouldn't that provide a way to obfuscate IP addresses while maintaining
> uniqueness (i. e. a given IP gets alway hashed to the same hash).
>
> Tim said in a message on enwiki-l that he has looked into the matter but
> haven't found any satisfying solution.
>
> So what's the problem with salted hashes?
>
> Note: I have read something about hashing but I am far from being an
> expert, please assume I am the classical layman.
>
> Thanks in advance to anyone who will take the time to explain.
>
> C
> ---------- Messaggio inoltrato ----------
> Da: "Lila Tretikov" <[email protected]>
> Data: 05/Apr/2015 11:30
> Oggetto: Re: [Wikimedia-l] Announcing: The Wikipedia Prize!
> A: "Wikimedia Mailing List" <[email protected]>
> Cc:
>
> All,
>
> As Tim mentioned we are seriously looking at
> privacy/identity/security/anonymity issues, specifically as it pertains to
> IP address exposure -- both from legal and technical standpoint. This
won't
> happen overnight as we need to get people to work on this and there are a
> lot of asks, but this is on our radar.
>
> On a related note, let's skip the sarcasm and treat each other with
> straightforward honestly. And for non-English speakers -- who are also (if
> not more) in need of this -- sarcasm can be very confusing.
>
> Thanks,
> Lila
>
> On Fri, Apr 3, 2015 at 4:02 PM, Cristian Consonni <[email protected]
>
> wrote:
>
> > Hi Brian,
> >
> > 2015-03-30 0:25 GMT+02:00 Brian <[email protected]>:
> > > Although the initial goal of the Netflix Prize was to design a
> > > collaborative filtering algorithm, it became notorious when the data
was
> > > used to de-anonymize Netflix users. Researchers proved that given
just a
> > > user's movie ratings on one site, you can plug those ratings into
> another
> > > site, such as the IMDB. You can then take that information, and with
> some
> > > Google searches and optionally a bit of cash (for websites that sell
> user
> > > information, including, in some cases, their SSN) figure out who they
> > are.
> > > You could even drive up to their house and take a selfie with them, or
> > > follow them to work and meet their boss and tell them about their
views
> > on
> > > the topics they were editing.
> >
> > somewhat tangentially, and to bring back this to topic to a more
> > scientific setting I would like to point out that there has already
> > been reasearch in the past on this topic.
> >
> > I highly recommend reading the following paper:
> >
> > Lieberman, Michael D., and Jimmy Lin. "You Are Where You Edit:
> > Locating Wikipedia Contributors through Edit Histories." ICWSM. 2009.
> > (PDF <
> >
>
http://www.pensivepuffin.com/dwmcphd/syllabi/infx598_wi12/papers/wikipedia/lieberman-lin.YouAreWhereYouEdit.ICWSM09.pdf
> > >)
> >
> > For those of you that don't want to read the whole paper, you can find
> > a recap of the most relevant findings in this presentation by Maurizio
> > Napolitano:
> > <
> >
http://www.slideshare.net/napo/social-geography-wikipedia-a-quick-overwiew
> > >
> >
> > The main idea is associating spatial coordinates to a Wikipedia
> > articles when possible, this articles are called "geopages". Then you
> > extract from the history of articles the users which have edited a
> > geopage. If you plot the geopages edited by a given contributor you
> > can see that they tend to cluster, so you can define an "edit area".
> > The study finds that 30-35% of contributors concentrate their edits in
> > an edit area smaller than 1 deg^2 (~12,362 km^2, approximately the
> > area of Connecticut or Northern Ireland[1] (thanks, Wikipedia!)).
> >
> > For another free/libre project with a geographic focus like
> > OpenStreetMap this is even more marked, check out for example this
> > tool «“Your OSM Heat Map” (aka Where did you contribute?)»[2] by
> > Pascal Neis.
> >
> > This, of course, is not a straightforward de-anonimization but this
> > methods work in principle for every contributor even if you obfuscate
> > their IP or username (provided that you can still assign all the edits
> > from a given user to a unique and univocal identifier)
> >
> > C
> > [1] https://en.wikipedia.org/wiki/Square_degree
> > [2a] http://yosmhm.neis-one.org/
> > [2b] http://neis-one.org/2011/08/yosmhm/
> >
> > _______________________________________________
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> > https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines
> > [email protected]
> > Unsubscribe: https://lists.wikimedia.org/mailman/listinfo/wikimedia-l,
> > <mailto:[email protected]?subject=unsubscribe>
> >
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