ned+ietf-smtp(_at_)mrochek(_dot_)com wrote:
Of course, if there were no
valid recipients, even "command out of sequence" (or equivalent)
would be plausible.
Other permanent failures are also possible, e.g., various things along
the lines of "Something you have said caused me to hate you and I'm
rejecting this tranaction in toto".
+1
Like this highly probable event within our own market of customers
which offers strong operator based policies at DATA with the system
wide intent to cover the entire user base, not just personal:
550 - Message rejected. Virus Detected - Don't try again
I've read proposed legislation (Canadian) that would imposed fines and
civil liability risk for all ISPs to make sure AVS software is
included to protect the layman users. i.e. not put the burden on them.
and quite possible, even related to new domain x822 based RFC
protocols like:
550 - Message rejected. SENDER-ID Domain Policy Rejection
550 - Message rejected. DKIM-ADSP Domain Policy Rejection
Both are quite possible and reasonable implementations for SENDERID or
DKIM verification/ADSP compliant receivers.
FWIW:
Barry Leiba issued an DKIM list announcement for the CEAS 2008
Conference (http://www.ceas.cc) today.
Perusing the web site, I noticed for the 2007 conference, there were a
few papers presented which are directly and/or indirectly to this topic:
IMV, this one hit the sore nail on the head.
o Combining Global and Personal Anti-Spam Filtering
Richard Segal
IBM Research
http://www.ceas.cc/2007/papers/paper-74.pdf
Abstract: Many of the first succesfull anti-spam filters were
personalized classifier's that were trained on an individual
user's spam and ham e-mail. Proponents of personalized filters
argue that statistical text learning is effective because it can
identify the unique aspects of each individual's e-mail. On the
other hand, a single classifier learned for a large population of
users can leverage the data provided by each individual user
across hundreds or even thousands of users. This paper
investigates the tradeoff between globally and personally trained
anti-spam classifiers. We find that globally-trained text
classification easily outperforms personally-trained
classification under realistic settings. This result does not
mean that personalization is not valuable. We show that the two
techniques can be combined to produce a modest improvement in
overall performance.
IMV, this one helps explain why not all email is alike, obviously.
o Email traffic: a quantitative snapshot
Richard Clayton,
University of Cambridge
http://www.ceas.cc/2007/papers/paper-76.pdf
Abstract: It is common to think of email as a one-to-one
communication medium, but at the ISP level, many email flows are
mailing-lists (one-to-many) or forwarded traffic (many-to-one).
Some anti-spam systems have foundered on misapprehensions as to
the nature and importance of these flows. However, although
understanding has grown, there are no quantitative studies in the
literature as to the relative importance of these different types
of email flow. This brief study is a snapshot of the types of
email that can be distinguished amongst the 331 million items
that arrived at a medium-sized ISP in March 2007, and is intended
to provoke the publication of further data, to better illuminate
the relative importance of different types of email.
--
Sincerely
Hector Santos, CTO
http://www.santronics.com
http://santronics.blogspot.com