Bjarni Rznar Einarsson writes:
Combine that sort of stuff with analysis of writing style, vocabulary, etc. and you might be able to correlate two e-mails as originating from the same person with some degree of accuracy.
I'm not aware of any research into the trackability of such things, as e-mail generally isn't considered anonymous anyway, but a lot of the work that has gone into fighting spam would actually have implications here as well.
Hi Bjarni, There is a stylometry item in the anonbib where they do statistical analysis of features of writing style: http://www.usenix.org/publications/library/proceedings/sec2000/full_papers/r... I bet these techniques have gotten more powerful as the field of machine learning has developed, although I don't know if there are more recent studies of what this means for anonymity. -- Seth Schoen Senior Staff Technologist schoen@eff.org Electronic Frontier Foundation https://www.eff.org/ 454 Shotwell Street, San Francisco, CA 94110 +1 415 436 9333 x107 *********************************************************************** To unsubscribe, send an e-mail to majordomo@torproject.org with unsubscribe or-talk in the body. http://archives.seul.org/or/talk/ ----- End forwarded message ----- -- Eugen* Leitl <a href="http://leitl.org">leitl</a> http://leitl.org ______________________________________________________________ ICBM: 48.07100, 11.36820 http://www.ativel.com http://postbiota.org 8B29F6BE: 099D 78BA 2FD3 B014 B08A 7779 75B0 2443 8B29 F6BE