Hi Adam,
One thought: you don't really need the date/time data at any detailed
resolution, do you? If what you're wanting it for is to track major
changes ("last month it all switched to this IP") and to purge old
data ("delete anything older than 10 March"), you could simply log day
rather than datetime.
enwiki / 127.0.0.1 / 123.45 / 2014-04-16:1245.45
enwiki / 127.0.0.1 / 123.45 / 2014-04-16
- the latter gives you the data you need while making it a lot harder
to do any kind of close user-identification.
Andrew.
On 16 Apr 2014 19:17, "Adam Baso" <abaso(a)wikimedia.org> wrote:
Inline.
Thanks for starting this thread.
Sorry if I've overlooked this, but who/what will have access to this
data?
Only members of the mobile team? Local project
CheckUsers? Wikimedia
Foundation-approved researchers? Wikimedia shell users? AbuseFilter
filters?
It's a good question. The thought is to put it in the customary wfDebugLog
location (with, for example, filename "mccmnc.log") on fluorine.
It just occurred to me that the wiki name (e.g., "enwiki"), but not the
full URL, gets logged additionally as part of the wfDebugLog call; to make
the implicit explicit, wfDebugLog adds a datetime stamp as well, and that's
useful for purging old records. I'll forward this email to mobile-l and
wikitech-l to underscore this.
And this may be a silly question, but is there a
reasonable means of
approximating how identifying these two data points alone are? That is,
Using a mobile country code and exit IP address, is it possible to
identify a particular editor or reader? Or perhaps rephrased, is this
data
considered anonymized?
Not a silly question. My approximation is these tuples (datetime, now that
it hit me - XYwiki, exit IP, and MCC-MNC) alone, although not perfectly
anonymized, are low identifying (that is, indirect inferences on the data
in isolation are unlikely, but technically possible, through examination of
short tail outliers in a cluster analysis where such readers/editors exist
in the short tail outliers sets), in contrast to regular web access logs
(where direct inferences are easy).
Thanks. I'll forward this along now.
-Adam
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