Internet DRAFT - draft-kucherawy-repute-considerations
draft-kucherawy-repute-considerations
REPUTE M. Kucherawy
Internet-Draft November 7, 2012
Intended status: Informational
Expires: May 11, 2013
Operational Considerations Regarding Reputation Services
draft-kucherawy-repute-considerations-00
Abstract
The use of reputation systems is has become a common tool in many
applications that seek to apply collected intelligence about traffic
sources. Often this is done because it is common or even expected
operator practice. It is therefore important to be aware of a number
of considerations for both operators and consumers of the data. This
document includes a collection of the best advice available regarding
providers and consumers of reputation data, based on experience to
date. Much of this is based on experience with email reputation
systems, but the concepts are generally applicable.
Status of This Memo
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This Internet-Draft will expire on May 11, 2013.
Copyright Notice
Copyright (c) 2012 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
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to this document. Code Components extracted from this document must
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described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Background . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. Evolution . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
4. Reputation Clients . . . . . . . . . . . . . . . . . . . . . . 4
5. Reputation Service Providers . . . . . . . . . . . . . . . . . 6
6. Security Considerations . . . . . . . . . . . . . . . . . . . . 6
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . . 6
8. Informative References . . . . . . . . . . . . . . . . . . . . 7
Appendix A. Acknowledgements . . . . . . . . . . . . . . . . . . . 7
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1. Introduction
Reputation services involve collecting feedback from the community
about sources of Internet traffic and aggregating that feedback into
a rating of some kind. Common examples include feedback about
traffic associated with specific email addresses, URIs or parts of
URIs, IP addresses, etc. The specific collection, analysis, and
rating methods vary from one service to the next and one problem
domain to the next, but several operational concepts appear to be
common to all of these.
The promise of the protection that reputation services offers can be
enticing, and many users and operators alike typically engage those
services merely because it is expected of them. A critical notion,
however, is that doing so explicitly involves a third party in the
flow of data those parties receive. This is often taken for granted,
with potentially disastrous results.
This document highlights this and other considerations in providing
and consuming reputation data services.
2. Background
The community has historically focused on identifying sources that
misbehave, i.e., that earn negative reputations. The purpose here is
to identify and filter traffic from bad actors. This grew out of
operational need. As the Internet grew, so did the occurence of
problematic traffic, especially in email. The pragmatics of email
(i.e., the fact that the total IP address space is more constrained
than the total email address space) drove the focus on using IP
addresses as the focus of reputation, in addition to the fact that IP
addresses have a degree of validation (via the TCP/IP infrastructure)
where email addresses have had none.
A specific example of a reputation service in common use in the email
space is the DNS blacklist [DNSBL]. This is a method of querying a
database as to whether a source of incoming [SMTP] email traffic
should be allowed to relay email, based on previous observations and
feedback. The method uses the IP address of the source as the basis
for a query to the database using the Domain Name System [DNS] as the
interface. [DNSBL] includes several points in its Security
Considerations document that are repeated and further developed here.
However, regardless of the identifier used as the identifier for a
reputation, bad actors can evade detection or the effects of their
observed behavior by changing identifiers (e.g., move to a new IP
address, register a new domain name, use a sub-domain). This makes
the problem space effectively boundless, especially as IPv6 rolls
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out.
3. Evolution
More modern thinking is evolving toward the identification of good
actors rather than bad actors, and giving them preferential
treatment. This drastically reduces the problem space: There are
vastly more IP addresses and email addresses used by bad actors to
generate problematic traffic than are used by good actors to generate
desirable traffic.
Moreover, good actors tend to be represented by stable names and
addresses, allowing users to rely on these to identify and give
preferential treatment to their traffic. Good actors have no need to
hop around to different addresses, and already work to keep their
traffic clean.
This notion has only been tried to date using manually edited
whitelists, but has shown promising results on that scale.
4. Reputation Clients
understand that you are granting a third party the ability to affect
your incoming traffic, for better or worse
this is the point, of course, when everything works properly
some cases have occurred where a reputation service provider (RSP)
shut down operation, and to encourage consumers to stop querying, it
began reporting a maximal negative reputation about all subjects,
causing rejection of all incoming traffic during the incident period
reputation providers will be the subject of attacks when it's
understood that sucess doing so will allow malicious content to evade
detection and filtering; clients need to be aware of possible
interruptions in service availability or quality
understand that some actors will try to game the service, which means
that a reputation service is inherently fragile; for operational
clients, this should prompt balanced and comparative, rather than
unilateral, use of the service
try to learn the following things about your RSP, to understand your
exposure potential:
o their basis for listing or not listing particular subjects
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o if an RSP is paid by its listees, what are the rate and criteria
for rejection?
o how the provider collects data about subjects
o how many data points are input to the reported reputation
o is reputation based on a reliable identifier?
o how it etablishes reliability and authenticity of those data
o how data validity is maintained (e.g., on-going monitoring of the
reported data and sources)
o how actively data validity is tracked (e.g., how changes are
detected)
o how disputed reputations are handled
o how data expire
o is older information more or less influential than newer?
o is the reported reputation a scalar, a Boolean value, a collection
of values, or something else?
o when transitioning among RSPs, determine the differences between
them among these above points; that is, does a particular score
from one mean the same thing from the other?
ensure the capability of local overrides for cases where the client
expects to disagree with the reported reputation
be able limit the impact of a negative reputation on content
acceptance; for example, rather than rejecting content outright when
a negative reputation is returned, simply subject it to additional
local analyis
have a sensible default to apply when the RSP is not available
consider tailoring operation to prefer or emphasize content whose
sources have positive reputations; recall that negative reputations
are easy to shed, and the universe of things that will earn and
maintain positive reputations is relatively small
consider querying and cross-referencing multiple RSPs; this helps to
detect which are reliable, and offsets the effect of anomalous
replies
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5. Reputation Service Providers
make the answers to the questions in Section 4 available on demand to
consumers
base reputations on accurate identifiers, i.e., something difficult
to forge
it is important to have a transparent remediation process for
disputes of computed reputations
provide the ability to request details in the returned result about
how the result was reached, allowing the client to decide if the
result should be applied, such as:
o the result itself
o the number of data points used to compute the result
o the age range of the data
o source diversity of the input data
o currency of the result (i.e., when it was computed)
o basis of the result (i.e., which identifier was used)
harden systems and algorithms as much as practicable against gaming
or data poisoning; larger source diversities are harder to overcome
with poisoned input, but are expensive to build
systems based on positive reputations are promising since positive
reputations, if made difficult to earm put a large cost on bad actors
6. Security Considerations
Several points are raised above that can be described as threats to
the delivery of valid user data. This document highlights and
discusses those issues, but introduces no new security issues.
7. IANA Considerations
This memo contains no actions for IANA.
[RFC Editor: Please remove this section prior to publication.]
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8. Informative References
[DNS] Mockapetris, P., "Domain Names -- Concepts and Facilities",
RFC 1034, November 1987.
[DNSBL] Levine, J., "DNS Blacklists and Whitelists", RFC 5782,
February 2010.
[SMTP] Klensin, J., "Simple Mail Transfer Protocol", RFC 5321,
October 2008.
Appendix A. Acknowledgements
The author wishes to acknowledge the following for their review and
constructive criticism of this proposal: (names)
Author's Address
Murray S. Kucherawy
EMail: superuser@gmail.com
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