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Versions: 00 01                                                         
SIPPING                                                     J. Rosenberg
Internet-Draft                                               dynamicsoft
Expires: January 9, 2005                                     C. Jennings
                                                           July 11, 2004

             The Session Initiation Protocol (SIP) and Spam

Status of this Memo

   By submitting this Internet-Draft, I certify that any applicable
   patent or other IPR claims of which I am aware have been disclosed,
   and any of which I become aware will be disclosed, in accordance with
   RFC 3668.

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   This Internet-Draft will expire on January 9, 2005.

Copyright Notice

   Copyright (C) The Internet Society (2004).  All Rights Reserved.


   Spam, defined as the transmission of bulk unsolicited messages, has
   plagued Internet email.  Unfortunately, spam is not limited to email.
   It can affect any system that enables user to user communications.
   The Session Initiation Protocol (SIP) defines a system for user to
   user multimedia communications.  Therefore, it is susceptible to
   spam, just as email is.  In this document, we analyze the problem of
   spam in SIP.  We first identify the ways in which the problem is the
   same and the ways in which it is different from email.  We then

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   examine the various possible solutions that have been discussed for
   email and consider their applicability to SIP.  Discussions on this
   draft should be directed at sipping@ietf.org.

Table of Contents

   1.   Introduction . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.   Problem Definition . . . . . . . . . . . . . . . . . . . . .   3
     2.1  Call Spam  . . . . . . . . . . . . . . . . . . . . . . . .   4
     2.2  IM Spam  . . . . . . . . . . . . . . . . . . . . . . . . .   6
     2.3  Presence Spam  . . . . . . . . . . . . . . . . . . . . . .   7
   3.   Solution Space . . . . . . . . . . . . . . . . . . . . . . .   7
     3.1  Content Filtering  . . . . . . . . . . . . . . . . . . . .   7
     3.2  Black Lists  . . . . . . . . . . . . . . . . . . . . . . .   7
     3.3  White Lists  . . . . . . . . . . . . . . . . . . . . . . .   8
     3.4  Consent-Based Communications . . . . . . . . . . . . . . .   9
     3.5  Turing Tests . . . . . . . . . . . . . . . . . . . . . . .  10
     3.6  Computational Puzzles  . . . . . . . . . . . . . . . . . .  11
     3.7  Payments at Risk . . . . . . . . . . . . . . . . . . . . .  12
     3.8  Legal Action . . . . . . . . . . . . . . . . . . . . . . .  13
     3.9  Circles of Trust . . . . . . . . . . . . . . . . . . . . .  13
     3.10   Centralized SIP Providers  . . . . . . . . . . . . . . .  14
     3.11   Sender Checks  . . . . . . . . . . . . . . . . . . . . .  15
   4.   Authenticated Identity in SIP  . . . . . . . . . . . . . . .  15
   5.   Recommendations  . . . . . . . . . . . . . . . . . . . . . .  16
   6.   Security Considerations  . . . . . . . . . . . . . . . . . .  16
   7.   Acknowledgements . . . . . . . . . . . . . . . . . . . . . .  17
   8.   Informative References . . . . . . . . . . . . . . . . . . .  17
        Authors' Addresses . . . . . . . . . . . . . . . . . . . . .  18
        Intellectual Property and Copyright Statements . . . . . . .  20

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1.  Introduction

   Spam, defined as the transmission of bulk unsolicited email, has been
   a plague on the Internet email system, rendering it nearly useless.
   Many solutions have been documented and deployed to counter the
   problem.  None of these solutions is ideal.  However, one thing is
   clear: the spam problem would be much less significant had solutions
   been deployed ubiquitously before the problem became widespread.

   The Session Initiation Protocol (SIP) [2] is used for multimedia
   communications between users, including voice, video, instant
   messaging and presence.  Although it has seen widespread deployment,
   the deployments today have mostly been in disconnected islands.
   Providers have not yet connected to each other in significant ways,
   nor have they yet opened up access so as to allow receipt of SIP
   messaging from the open Internet.  Possibly as a result of this, SIP
   networks have not yet been the target of any significant amount of
   spam.  However, we believe that it is just a matter of time.

   It is important that the SIP community react now, rather than later,
   and define and deploy anti-spam measures before the problem arises.
   This document serves to help frame the problem of spam in SIP and
   analyze the solution space in order to help determine a path forward.

2.  Problem Definition

   The spam problem in email is well understood, and we make no attempt
   to further elaborate on it here.  The question, however, is what is
   the meaning of spam when applied to SIP? Since SIP covers a broad
   range of functionality, there appear to be three related but
   different manifestations:
   Call Spam: This type of spam is defined as a bulk unsolicited set of
      session initiation attempts (i.e., INVITE requests), attempting to
      establish a voice, video, instant messaging [1] or other type of
      communications session.  If the user should answer, the spammer
      proceeds to relay their message over the real time media.  This is
      the classic telemarketer spam, applied to SIP.
   IM Spam: This type of spam is similar to email.  It is defined as a
      bulk unsolicited set of instant messages, whose content contains
      the message that the spammer is seeking to convey.  IM spam is
      most naturally sent using the SIP MESSAGE [3] request.  However,
      any other request which causes content to automatically appear on
      the user's display will also suffice.  That might include INVITE
      requests with large Subject headers (since the Subject is
      sometimes rendered to the user), or INVITE requests with text or
      HTML bodies.

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   Presence Spam: This type of spam is similar to IM spam.  It is
      defined as a bulk unsolicited set of presence requests (i.e.,
      SUBSCRIBE requests [4] for the presence event package [7]), in an
      attempt to get on the "buddy list" or "white list" of a user in
      order to send them IM or initiate other forms of communications.
      Unlike IM spam, presence spam does not actually convey content in
      the messages.  As such, it is not clear how useful or valuable
      this kind of spam is.

   There are many other SIP messages that a spammer might send.
   However, most of the other ones do not result in content being
   delivered to a user, nor do they seek input from a user.  Rather,
   they are answered by automata.  OPTIONS is a good example of this.
   There is little value for a spammer in sending an OPTIONS request,
   since it is answered automatically by the UAS.  No content is
   delivered to the user, and they are not consulted.

   In the sections below, we consider the likelihood of these various
   forms of SIP spam.  This is done in some cases by a rough cost
   analysis.  It should be noted that all of these analyses are
   approximate, and serve only to give a rough sense of the order of
   magnitude of the problem.

2.1  Call Spam

   Will call spam occur? That is an important question to answer.
   Clearly, it does occur in the existing telephone network, in the form
   of telemarketer calls.  Although these calls are annoying, they do
   not arrive in the same kind of volume as email spam.  The difference
   is cost; it costs more for the spammer to make a phone call than it
   does to send email.  This cost manifests itself in terms of the cost
   for systems which can perform telemarketer call, and in cost per

   Unfortunately, both of these costs are substantially reduced by SIP.
   A SIP call spam application is easy to write.  It is just a UAC that
   initiates, in parallel, a large number of calls.  If a call connects,
   the spam application generates an ACK and proceeds to play out a
   recorded announcement, and then it terminates the call.  This kind of
   application can be built entirely in software, using readily
   available (and indeed, free) off the shelf components.  It can run on
   a low end PC and requires no special expertise to execute.

   The cost per call is also substantially reduced.  A normal
   residential phone line allows only one call to be placed at a time.
   If additional lines are required, a user must purchase more expensive
   connectivity.  Typically, a T1 or T3 would be required for a large
   volume telemarketing service.  That kind of access is very expensive

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   and well beyond the reach of an average user.  A T1 line is
   approximately US $250 per month, and about 1.5 cents per minute for
   calls.  T1 lines used only for outbound calls (such as in this case)
   are even more expensive than inbound trunks due to the reciprocal
   termination charges that a provider pays and receives.

   There are two aspects to the capacity: the call attempt rate, and the
   number of simultaneous successful calls that can be in progress.  A
   T1 would allow a spammer at most 24 simultaneous calls, and assuming
   about 10s for each call attempt, about 2.4 call attempts per second.
   At high volume calling, the per-minute rates far exceed the flat
   monthly fee for the T1.  The result is a cost of 250,000 microcents
   for each successful spam delivery, assuming 10s of content.

   With SIP, this cost is much reduced.  Consider a spammer using a
   typical broadband Internet connection that provides 500Kbps of
   upstream bandwidth.  Initiating a call requires just a single INVITE
   message.  Assuming, for simplicity's sake, that this is 1kB, a
   500Kbps upstream DSL or cable modem connection will allow about 62
   call attempts per second.  A successful call requires enough
   bandwidth to transmit a message to the receiver.  Assuming a low
   compression codec (say, G.723.1 at 5.6 Kbps), as many as 90
   simultaneous calls can be in progress.  With 10s of content per call,
   that allows for 9 successful call attempts per second.  This means
   that a system could deliver a voice message successfully to users at
   a rate of around 9 per second.  If broadband access is around $50/
   month, the cost per successful voice spam is about 215 microcents
   each.  This assumes that calls can be made 24 hours a day, which may
   or may not be the case.

   These figures indicate that SIP call spam is roughly three orders of
   magntiude cheaper to send than traditional circuit-based telemarketer
   calls.  This low cost is certainly going to be very attractive to

   These figures assume that the primary limitation is the access
   bandwidth and not CPU, disk, or termination costs.  Termination costs
   merit further discussion.  Currently, most VoIP calls terminate on
   the Public Switched Telephone Network (PSTN), and this termination
   costs the originator of the call money.  These costs are similar to
   the per-minute rates of a T1.  It ranges anywhere from half a cent to
   three cents per minute, depending on volume and other factors.
   However, equipment costs, training and other factors are much lower
   for SIP-based termination than a T1, making the cost still lower than
   circuit connectivity.  Furthermore, the current trend in VoIP systems
   is to make termination free for calls that never touch the PSTN, that
   is, calls to actual SIP endpoints.  Thus, as more and more SIP
   endpoints come online (there are probably around 5 million

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   addressable SIP endpoints on the Internet as of writing), termination
   costs will probably drop.  Until then, SIP spam can be used in
   concert with termination services for a lower cost form of
   traditional telemarketer calls, made to normal PSTN endpoints.

   This number (9 deliveries per second) is below the successful message
   delivery rate of email [[NOTE: is there a figure for this]].
   However, many spam messages are automatically deleted by filters or
   users without ever being read.  It is far more likely that a call
   spam will be examined by a user if its delivered, due to the
   difficulty in automated content filtering (see below).  Thus, when
   one examines the final figure of importance - the number of new
   customers attracted per spam delivered, it is far from clear whether
   call spam or email spam will be more effective.

   Another part of the cost of spamming is collecting addresses.
   Spammers have, over time, built up immense lists of email addresses,
   each of the form user@domain, to which spam is directed.  SIP uses
   the same form of addressing, making it likely that email addresses
   can easily be turned into valid SIP addresses.  Telephone numbers
   also represent valid SIP addresses, in that, in concert with a
   termination provider, a spammer can direct SIP calls at traditional
   PSTN devices.  It is not clear whether email spammers have also been
   collecting phone numbers as they perform their web sweeps, but it is
   probably not hard to do so.  Furthermore, unlike email addresses,
   phone numbers are a finite address space and one that is fairly
   densely packed.  As a result, going sequentially through phone
   numbers is likely to produce a fairly high hit rate.  Thus, it seems
   like the cost is relatively low for a spammer to obtain large numbers
   of SIP addresses to which spam can be directed.

2.2  IM Spam

   IM spam is very much like email, in terms of the costs for deploying
   and generating spam.  Assuming, for the sake of argument, a 1kB
   message to be sent and 500 Kbps of upstream bandwidth, thats 62
   messages per second.  At $50/month, the result is 31 microcents per
   message.  This is less than voice spam, but not substantially less.
   The cost is probably on par with email spam.  However, IM is much
   more intrusive than email.  In today's systems, IMs automatically pop
   up and present themselves to the user.  Email, of course, must be
   deliberately selected and displayed.  However, many IM systems employ
   white lists, which only allow spam to be delivered if the sender is
   on the white list.  Thus, whether or not IM spam will be useful seems
   to depend a lot on the nature of the systems as the network is opened
   up.  If they are ubiquitously deployed with white-list access, the
   value of IM spam is likely to be low.

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2.3  Presence Spam

   Since the value of presence spam is unclear to the authors at this
   moment, we do not comment on it further here.

3.  Solution Space

   In this section, we consider the various solutions that might be
   possible to deal with SIP spam.  We primarily consider techniques
   that have been employed to deal with email spam.  It is important to
   note that the solutions documented below are not meant to be an
   exhaustive study of the spam solutions used for email but rather just
   a representative set.  We also consider some solutions that appear to
   be SIP-specific.

3.1  Content Filtering

   The most common form of spam protection used in email is based on
   content filtering.  These spam filters analyze the content of the
   email, and look for clues that the email is spam.  Bayesian spam
   filters are in this category.

   Unfortunately, this type of spam filtering is almost completely
   useless for call spam.  There are two reasons.  First, in the case
   where the user answers the call, the call is already established and
   the user is paying attention before the content is delivered.  The
   spam cannot be analyzed before the user sees it.  Second, if the
   content is stored before the user accesses it (e.g., with voicemail),
   the content will be in the form of recorded audio or video.  Speech
   and video recognition technology is not likely to be good enough to
   analyze the content and determine whether or not it is spam.  Indeed,
   if a system tried to perform speech recognition on a recording in
   order to perform such an analysis, it would be easy for the spammers
   to make calls with background noises, poor grammar and varied
   accents, all of which will throw off recognition systems.  Video
   recognition is even harder to do and remains primarily an area of

   Therefore, our conclusion is that the most successful form of
   anti-spam measures used in email are almost useless for call spam.

   IM spam, due to its similarity to email, can be countered with
   content analysis tools.  Indeed, the same tools and techniques used
   for email will directly work for IM spam.

3.2  Black Lists

   Black listing is an approach whereby the spam filter maintains a list

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   of addresses that identify spammers.  These addresses include both
   usernames (spammer@domain.com) and entire domains (spammers.com).
   Pure blacklists are not very effective in email for two reasons.
   First, email addresses are easy to spoof, making it easy for the
   sender to pretend to be someone else.  If the sender varies the
   addresses they send from, the black list becomes almost completely
   useless.  The second problem is that, even if the sender doesn't
   forge the from address, email addresses are in almost limitless
   supply.  Each domain contains an infinite supply of email addresses,
   and new domains can be obtained for very low cost.  Furthermore,
   there will always be public providers that will allow users to obtain
   identities for almost no cost (for example, Yahoo or AOL mail
   accounts).  The entire domain cannot be blacklisted because it
   contains so many valid users.  Blacklisting needs to be for
   individual users.  Those identities are easily changed.

   Blacklists are also likely to be ineffective for SIP spam.
   Fortunately, SIP has much stronger mechanisms for inter-domain
   authenticated identity than email has (see Section 4).  Assuming
   these mechanisms are used and enabled in inter-domain communications,
   it becomes nearly impossible to forge sender addresses.  However, it
   still remains cheap to obtain a nearly infinite supply of addresses.

3.3  White Lists

   White lists are the opposite of black lists.  It is a list of valid
   senders that a user is willing to accept email from.  In the email
   world, white lists alone are not useful, since they would prohibit a
   user from ever being able to receive email from someone who was not
   explicitly put on the white list.  It is also too easy for spammers
   to forge sender addresses.  White lists also demand time from the
   user to manage them.

   Fortunately, white lists are much more useful in preventing SIP spam.
   This is for several reasons.  First, there is a natural "white list"
   in SIP systems - the buddy list.  Many SIP clients use the buddy list
   concept as the center point for communications.  This trend is likely
   to continue.  Because of its common usage in SIP communications,
   users have been willing to invest the time in managing their lists,
   growing them, and keeping them up to date.  This is because they have
   utility in many ways, not just as a form of white list.

   Second, because SIP can provide a much more secure form of
   authenticated identity, even for inter-domain communications, the
   problem of forged senders can be eliminated, making the white list
   more useful.

   There is still the problem of how to communicate with users who are

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   not known ahead of time.  In email, techniques like the Turing tests
   have been employed for this purpose.  Those are considered further in
   the sections below.  Since white lists alone are not a solution,
   because of the "initial communication" problem, one of these
   techniques will need to be used in conjunction with any white list
   solution in SIP.

3.4  Consent-Based Communications

   A consent-based solution is used in conjunction with white or black
   lists.  That is, if user A is not on user B's white or black list,
   and user A attempts to communicate with user B, user A's attempt is
   initially rejected, and they are told that consent is being
   requested.  Next time user B connects, user B is informed that user A
   attempted to communicate, and then user B can authorize user A.

   These kinds of consent-based systems are used widely in presence and
   IM but not in email.  This is likely due to the need for a secure
   authenticated identity mechanism, which is a pre-requisite for this
   kind of solution.  Since most of today's IM systems are closed,
   sender identities can be authenticated.

   This kind of consent-based communications has been standardized in
   SIP for presence, using the watcher information event package [8] and
   data format [9], which allow a user to find out that someone has
   subscribed.  Then, the XML Configuration Access Protocol (XCAP) [10]
   is used, along with the XML format for presence authorization [11] to
   provide permission for the user to communicate.  However, to date,
   these techniques have been applied strictly for presence.

   If they were extended to cover IM and calling, would it help? It is
   hard to say.  At first glance, it would seem to help a lot.  However,
   it might just change the nature of the spam.  Instead of being
   bothered with content, in the form of call spam or IM spam, users are
   bothered with consent requests.  A user's "communications inbox"
   might instead be filled with requests for communications from a
   multiplicity of users.  On the flip side, those requests for
   communications don't convey any useful content to the user.  In order
   for the spammer to convey content to the user, the user must
   explicitly accept the request, and only then can the spammer convey
   the content.  This is unlike email spam, where, even though much spam
   is automatically deleted, some percentage of the content does get
   through, and is seen by users, without their explicit consent that
   they want to see it.  Thus, if consent is required first, and nearly
   all users do not give consent to spammers, the value in sending spam
   is reduced, and perhaps it will cease.

   As such, the real question is whether or not the consent system would

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   make it possible for a user to give consent to non-spammers and
   reject spammers.  Authenticated identity can help.  A user in an
   enterprise would know to give consent to senders in other enterprises
   in the same industry, for example.  However, in the consumer space,
   if sip:bob@aol.com tries to communicate with a user, how does that
   user determine whether bob is a spammer or a long-lost friend from
   high school? There is no way based on the identity alone.  In such a
   case, a useful technique is to grant permission for bob to
   communicate but to make the permission is extremely limited.  In
   particular, bob may be granted permission to send no more than 200
   words of text in a single IM, which he can use to identify himself,
   so that the user can determine whether or not more permissions are
   appropriate.  However, this 200 words of text may be enough for a
   spammer to convey their message.

   Thus, it seems that a consent-based framework, along with white lists
   and black lists, cannot fully solve the problem for SIP, although it
   does appear to help.

3.5  Turing Tests

   In email, Turing tests are those solutions whereby the sender of the
   message is given some kind of puzzle or challenge, which only a human
   can answer.  If the puzzle is answered correctly, the sender is
   placed on the user's white list.  These puzzles frequently take the
   form of recognizing a word or sequence of numbers in an image with a
   lot of background noise.  Automata cannot easily perform the image
   recognition needed to extract the word or number sequence, but a
   human user can.

   Like many of the other email techniques, Turing tests are dependent
   on sender identity, which cannot easily be authenticated in email.

   Turing tests can be used to prevent IM spam, in much the same way
   they can be used to prevent email spam.  Indeed, the presence strong
   authenticated identity techniques in SIP will make such a Turing test
   approach more effective in SIP than in email.

   Turing tests can be applied to call spam as well, although not
   directly, because call spam does not usually involve the transfer of
   images and other content that can be used to verify that a human is
   on the other end.  If most of the calls are voice, the technique
   needs to be adapted to voice.  This is not that difficult to do.
   Here is how it could be done.  User A calls user B and is not on user
   B's white or black list.  User A is transferred to an IVR system.
   The IVR system tells the user that they are going to hear a series of
   numbers (say 5 of them), and that they have to enter those numbers on
   the keypad.  The IVR system reads out the numbers while background

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   music is playing, making it difficult for an automated speech
   recognition system to be applied to the media.  The user then enters
   the numbers on their keypad.  If they are entered correctly, the user
   is added to the whitelist.

   This kind of voice-based Turing test is easily extended to a variety
   of media, such as video and text, and user interfaces by making use
   of the SIP application interaction framework [12].  This framework
   allows client devices to interact with applications in the network,
   where such interaction is done with stimulus signaling, including
   keypads (supported with the Keypad Markup Language [13]), but also
   including web browsers, voice recognition, and so on.  The framework
   allows the application to determine the media capabilities of the
   device and interact with them appropriately.

   In the case of voice, there are problems with the Turing test
   described above.  First, it is language specific.  The application
   could be made to run in different languages, if the caller indicates
   their supported languages.  This is possible in SIP, using the
   Accept-Language header field, but this is not widely used at the

   The other problem with this Turing test is the same one that email
   tests have: instead of having an automata process the test, a spammer
   can pay cheap workers to take the tests.  Assuming cheap labor in a
   poor country can be obtained for about $100 US dollars per year, and
   assuming a Turing test of 30 second duration, this ends up being
   about ten thousand messages per dollar, or about 10,000 microcents
   per message.  Though much more expensive than the 31 microcents per
   message to send an IM spam, it is still relatively inexpensive.
   Turing tests may never completely solve the problem.

3.6  Computational Puzzles

   This technique is similar to Turing tests.  When user A tries to
   communicate with user B, user B asks user A to perform a computation
   and pass the result back.  This computation has to be something a
   human user cannot perform and something expensive enough to increase
   user A's cost to communicate.  This cost increase has to be high
   enough to make it prohibitively expensive for spammers but
   inconsequential for legitimate users.

   This technique works for email, and it can also work for all forms of
   SIP spam.  However, one of the problems is that there is wide
   variation in the computational power of the various clients that
   might legitimately communicate.  The CPU speed on a low end cell
   phone is around 50 MHz, while a high end PC approaches 5 GHz.  This
   represents almost two orders of magnitude difference.  Thus, if the

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   test is designed to be reasonable for a cell phone to perform, it is
   two orders of magnitude cheaper to perform for a spammer on a high
   end machine.  Recent research has focused on defining computational
   puzzles that challenge the CPU/memory bandwidth, as opposed to just
   the CPU [16].  It seems that there is less variety in the CPU/memory
   bandwidth across devices, roughly a single order of magnitude.

   These techniques might work.  They are an active area of research
   right now, and any results for email are likely to be directly
   applicable to SIP.  Of course, it is likely that these techniques
   will come with a lot of patents and other intellectual property

3.7  Payments at Risk

   This approach has been proposed for email [17].  When user A sends to
   user B, user A deposits a small amount of money (say, one dollar)
   into user B's account.  If user B decides that the message is not
   spam, user B refunds this money back to user A.  If the message is
   spam, user B keeps the money.  This technique requires two
   transactions to complete: a transfer from A to B, and a transfer from
   B back to A.  The first transfer has to occur before the message can
   be received in order to avoid reuse of "pending payments" across
   several messages, which would eliminate the utility of the solution.
   The second one then needs to occur when the message is found not to
   be spam.

   This technique appears just as applicable to call spam and IM spam as
   it is to email spam.  Like many of the other techniques, this
   exchange would only happen the first time you talk to people.  Its
   proper operation therefore requires a good authenticated identity

   This technique has the potential to truly make it prohibitively
   expensive to send spam of any sort.  However, it relies on cheap
   micro-payment techniques on the Internet.  Traditional costs for
   internet payments are around 25 cents per transaction, which would
   probably be prohibitive.  However, recent providers have been willing
   to charge 15% of the transaction for small transactions, for
   transactions as small as one cent.  This cost would have to be
   shouldered by users of the system.  The cost that would need to be
   shouldered per user is equal to the number of messages from unknown
   senders (that is, senders not on the white list) that are received.
   For a busy user, assume about 10 new senders per day.  If the deposit
   is 5 cents, the transaction provider would take .75 cents and deliver
   4.25 cents.  If the sender is allowed, the recipient returns 4.25
   cents, the provider takes 64 cents, and returns 3.6 cents.  This
   costs the sender .65 cents on each transaction, if it was legitimate.

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   If there are ten new recipients per day, thats US $1.95 per month,
   which is relatively inexpensive.

3.8  Legal Action

   In this solution, countries pass laws that prohibit spam.  These laws
   could apply to IM or call spam just as easily as they could apply to
   email spam.

   There is a lot of debate about whether these laws would really be
   effective in preventing spam.  Whether they are or are not effective,
   they would appear to be equally effective (or ineffective, as the
   case may be) in preventing SIP spam.

   As a recent example in the US, "do not call" lists seem to be
   effective.  However, due to the current cost of long distance phone
   calls, the telemarketing is coming from companies within the US.  As
   such, calls from such telemarketers can be traced.  If a telemarketer
   violates the "do not call" list, the trace allows legal action to be
   taken against them.  A similar "do not irritate" list for VoIP or for
   email would be less likely to work because the spam is likely to come
   from international sources.  This problem could be obviated if there
   was a strong way to identify the sender's legal entity, and then
   determine whether it was in a jurisdiction where it was practical to
   take legal action against them.  If the spammer is not in such a
   jurisdiction, the SIP spam could be rejected.

   There are also schemes that cause laws other than anti-spam laws to
   be broken if spam is sent.  This does not inherently reduce SPAM, but
   it allows more legal options to be brought to bear against the
   spammer.  For example, Habeas [18] inserts material in the header
   that, if a spammer inserted it without an appropriate license,
   allegedly causes the spammer to be violating US copyright and
   trademark laws, possibly reciprocal laws, and similar laws in many

3.9  Circles of Trust

   In this model, a group of domains (e.g., a set of enterprises) all
   get together.  They agree to exchange SIP calls amongst each other,
   and they also agree to introduce a fine should any one of them be
   caught spamming.  Each company would then enact measures to terminate
   employees who spam from their accounts.

   This technique relies on secure inter-domain authentication - that
   is, domain B can know that messages are received from domain A.  In
   SIP, this is readily provided by usage of the mutually authenticated
   TLS between providers.  Email does not have this kind of secure

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   domain identification, although new techniques are being investigated
   to add it using reverse DNS checks (see below).

   This kind of technique works well for small domains or small sets of
   providers, where these policies can be easily enforced.  However, it
   is unclear how well it scales up.  Could a very large domain truly
   prevent its users from spamming? Would a very large enterprise just
   pay the fine? How would the pricing be structured to allow both small
   and large domains alike to participate?

3.10  Centralized SIP Providers

   In this technique, a small number of providers get established as
   "inter-domain SIP providers".  These providers act as a
   SIP-equivalent to the interexchange carriers in the PSTN.  Every
   enterprise, consumer SIP provider or other SIP network (call these
   the local SIP providers) connects to one of these inter-domain
   providers.  The local SIP providers only accept SIP messages from
   their chosen inter-domain provider.  The inter-domain provider
   charges the local provider, per SIP message, for the delivery of SIP
   messages to other local providers.  The local provider can choose to
   pass on this cost to its own customers if it so chooses.

   The inter-domain SIP providers then form bi-lateral agreements with
   each other, exchanging SIP messages according to strict contracts.
   These contracts require that each of the inter-domain providers be
   responsible for charging a minimum per-message fee to their own
   customers.  Extensive auditing procedures can be put into place to
   verify this.  Besides such contracts, there may or may not be a flow
   of funds between the inter-domain providers.

   The result of such a system is that a fixed cost can be associated
   with sending a SIP message, and that this cost does not require
   micro-payments to be exchanged between local providers, as it does in
   Section 3.7.  Since all of the relationships are pre-established and
   negotiated, cheaper techniques for monetary transactions (such as
   monthly post-paid transactions) can be used.

   This technique can be made to work in SIP, whereas it cannot in
   email, because inter-domain SIP connectivity has not yet been
   established.  In email, there already exists a no-cost form of
   inter-domain connectivity that cannot be eliminated without
   destroying the utility of email.  If, however, SIP inter-domain
   communications get established from the start using this structure,
   there is a path to deployment.

   This structure is more or less the same as the one in place for the
   PSTN today, and since there is relatively little spam on the PSTN

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   (compared to email!), there is some proof that this kind of
   arrangement can work.  However, it puts back into SIP much of the
   complexity and monopolistic structures that SIP promised to
   eliminate.  As such, it is a solution that the authors find somewhat
   distasteful, though it may be a viable one.

3.11  Sender Checks

   In email, there has been a lot of interest in defining new DNS
   resource records that will allow a domain that receives a message to
   verify that the sender is a valid MTA for the sending domain.
   Standards are now being developed for this within the MARID working
   group in the IETF [14].

   Are these techniques useful for SIP? They can be used for SIP but are
   not necessary.  In email, there are no standards established for
   securely identifying the identity of the sending domain of a message.
   In SIP, however, TLS with mutual authentication can be used
   inter-domain.  A provider receiving a message can then reject any
   message coming from a domain that does not match the asserted
   identity of the sender of the message.  Such a policy only works in
   the "trapezoid" model of SIP, whereby there are only two domains in
   any call - the sending domain, which is where the originator resides,
   and the receiving domain.

   Thus, instead of creating DNS entries containing the IP address of
   each legitimate relay for a domain, the provider can give each
   legitimate relay a certificate that allows them to authenticate
   themselves as coming from that domain.  Such a technique would work
   even in the face of IP address spoofing, which the marid techniques
   are susceptible to.

4.  Authenticated Identity in SIP

   One of the key parts of many of the solutions described above is the
   ability to securely identify the identity of a sender of a SIP
   message.  SIP provides a secure solution for this problem, and it is
   important to discuss it here.

   The solution starts by having each domain authenticate its own users.
   SIP provides HTTP digest authentication as part of the core SIP
   specification, and all clients and servers are required to support
   it.  Indeed, digest is widely deployed for SIP.  However, digest
   alone has many known vulnerabilities, most notably offline dictionary
   attacks.  These vulnerabilities are all resolved by having each
   client maintain a persistent TLS connection to the server.  The
   client verifies the server identity using TLS, and then authenticates
   itself to the server using a digest exchange over TLS.  This

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   technique, which is also documented in RFC 3261, is very secure but
   not widely deployed yet.  In the long term, this approach will be
   necessary for the security properties needed to prevent SIP spam.

   Once a domain has authenticated the identity of a user, when it
   relays a message from that user to another domain, the sending domain
   can assert the identity of the sender, and include a signature to
   validate that assertion.  This is done using the SIP identity
   mechanism [15].  A weaker form of identity assertion is possible
   using the P-Asserted-Identity header field [6], but this technique
   requires mutual trust among all domains, and therefore has limited
   applicability.  Privacy is also possible, so that a user can request
   that their identity not be conveyed [5].

   SIP also defines the usage of TLS between domains, using mutual
   authentication, as part of the base specification.  This technique
   provides a way for one domain to securely determine that it is
   talking to a server that is a valid representative of another domain.

5.  Recommendations

   Unfortunately, there is no magic bullet for preventing SIP spam, just
   as there is none for email spam.  However, some concrete
   recommendations can be made.
   Strong Authenticated Identity is Key: In almost all of the solutions
      discussed above, there is a dependency on the ability to
      authenticate the sender of a SIP message inter-domain.  As such,
      we would argue that any provider that performs inter-domain SIP
      messaging MUST use the techniques described in Section 4.
   Extend the Consent Framework in Presence: The consent framework
      developed for presence, if applied to other aspects of SIP
      communications, would appear to be a useful tool in combating
      spam.  It doesn't seem likely that it can completely solve the
      problem, but it has worked well in presence systems so far.  Thus,
      we would recommend that the IETF proceed to develop such a
      framework for SIP.
   Leverage What Email has to Offer: Providers of SIP services should
      keep tabs on solutions in email as they evolve, and utilize the
      best of what those techniques have to offer.  But perhaps most
      importantly, providers should not ignore the spam problem until it
      happens! That is the pitfall email fell into.  As soon as a
      provider inter-connects with other providers, or allows SIP
      messages from the open Internet, that provider must consider how
      they will deal with spam.

6.  Security Considerations

   This memo is entirely devoted to issues relating to secure usage of

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   SIP services on the Internet.

7.  Acknowledgements

   The authors would like to thank Rohan Mahy for providing information
   on Habeas, Baruch Sterman for providing costs on VoIP termination
   services, and Gonzalo Camarillo for his review and comments.

8  Informative References

   [1]   Campbell, B., "The Message Session Relay Protocol",
         draft-ietf-simple-message-sessions-06 (work in progress), May

   [2]   Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston, A.,
         Peterson, J., Sparks, R., Handley, M. and E. Schooler, "SIP:
         Session Initiation Protocol", RFC 3261, June 2002.

   [3]   Campbell, B., Rosenberg, J., Schulzrinne, H., Huitema, C. and
         D. Gurle, "Session Initiation Protocol (SIP) Extension for
         Instant Messaging", RFC 3428, December 2002.

   [4]   Roach, A., "Session Initiation Protocol (SIP)-Specific Event
         Notification", RFC 3265, June 2002.

   [5]   Peterson, J., "A Privacy Mechanism for the Session Initiation
         Protocol (SIP)", RFC 3323, November 2002.

   [6]   Jennings, C., Peterson, J. and M. Watson, "Private Extensions
         to the Session Initiation Protocol (SIP) for Asserted Identity
         within Trusted Networks", RFC 3325, November 2002.

   [7]   Rosenberg, J., "A Presence Event Package for the Session
         Initiation Protocol (SIP)", draft-ietf-simple-presence-10 (work
         in progress), January 2003.

   [8]   Rosenberg, J., "A Watcher Information Event Template-Package
         for the Session Initiation  Protocol (SIP)",
         draft-ietf-simple-winfo-package-05 (work in progress), January

   [9]   Rosenberg, J., "An Extensible Markup Language (XML) Based
         Format for Watcher Information",
         draft-ietf-simple-winfo-format-04 (work in progress), January

   [10]  Rosenberg, J., "The Extensible Markup Language (XML)
         Configuration Access Protocol (XCAP)",

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         draft-ietf-simple-xcap-02 (work in progress), February 2004.

   [11]  Rosenberg, J., "Presence Authorization Rules",
         draft-ietf-simple-presence-rules-00 (work in progress), May

   [12]  Rosenberg, J., "A Framework for Application Interaction in the
         Session Initiation Protocol  (SIP)",
         draft-ietf-sipping-app-interaction-framework-01 (work in
         progress), February 2004.

   [13]  Burger, E., "A Session Initiation Protocol (SIP) Event Package
         for Key Press Stimulus  (KPML)", draft-ietf-sipping-kpml-03
         (work in progress), May 2004.

   [14]  Lyon, J., "MTA Authentication Records in DNS",
         draft-ietf-marid-core-01 (work in progress), June 2004.

   [15]  Peterson, J., "Enhancements for Authenticated Identity
         Management in the Session  Initiation Protocol (SIP)",
         draft-ietf-sip-identity-02 (work in progress), May 2004.

   [16]  Abadi, M., Burrows, M., Manasse, M. and T. Wobber, "Moderately
         Hard, Memory Bound Functions, NDSS 2003", February 2003.

   [17]  Abadi, M., Burrows, M., Birrell, A., Dabek, F. and T. Wobber,
         "Bankable Postage for Network Services, Proceedings of the 8th
         Asian Computing Science Conference, Mumbai, India", December

   [18]  <http://www.habeas.com>

Authors' Addresses

   Jonathan Rosenberg
   600 Lanidex Plaza
   Parsippany, NJ  07054

   Phone: +1 973 952-5000
   EMail: jdrosen@dynamicsoft.com
   URI:   http://www.jdrosen.net

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   Cullen Jennings
   170 West Tasman Dr.
   San Jose, CA  95134

   Phone: +1 408 527-9132
   EMail: fluffy@cisco.com

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