Network Working Group                                       J. Rosenberg
Request for Comments: 5039                                   C. Jennings
Category: Informational                                            Cisco
                                                            January 2008
             The Session Initiation Protocol (SIP) and Spam

Status of This Memo


This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited.




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 examine the various possible solutions that have been discussed for email and consider their applicability to SIP.


Table of Contents


   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
   2.  Problem Definition . . . . . . . . . . . . . . . . . . . . . .  3
     2.1.  Call Spam  . . . . . . . . . . . . . . . . . . . . . . . .  4
     2.2.  IM Spam  . . . . . . . . . . . . . . . . . . . . . . . . .  7
     2.3.  Presence Spam  . . . . . . . . . . . . . . . . . . . . . .  7
   3.  Solution Space . . . . . . . . . . . . . . . . . . . . . . . .  8
     3.1.  Content Filtering  . . . . . . . . . . . . . . . . . . . .  8
     3.2.  Black Lists  . . . . . . . . . . . . . . . . . . . . . . .  9
     3.3.  White Lists  . . . . . . . . . . . . . . . . . . . . . . .  9
     3.4.  Consent-Based Communications . . . . . . . . . . . . . . . 10
     3.5.  Reputation Systems . . . . . . . . . . . . . . . . . . . . 12
     3.6.  Address Obfuscation  . . . . . . . . . . . . . . . . . . . 14
     3.7.  Limited-Use Addresses  . . . . . . . . . . . . . . . . . . 14
     3.8.  Turing Tests . . . . . . . . . . . . . . . . . . . . . . . 15
     3.9.  Computational Puzzles  . . . . . . . . . . . . . . . . . . 17
     3.10. Payments at Risk . . . . . . . . . . . . . . . . . . . . . 17
     3.11. Legal Action . . . . . . . . . . . . . . . . . . . . . . . 18
     3.12. Circles of Trust . . . . . . . . . . . . . . . . . . . . . 19
     3.13. Centralized SIP Providers  . . . . . . . . . . . . . . . . 19
   4.  Authenticated Identity in Email  . . . . . . . . . . . . . . . 20
     4.1.  Sender Checks  . . . . . . . . . . . . . . . . . . . . . . 21
     4.2.  Signature-Based Techniques . . . . . . . . . . . . . . . . 21
   5.  Authenticated Identity in SIP  . . . . . . . . . . . . . . . . 22
   6.  Framework for Anti-Spam in SIP . . . . . . . . . . . . . . . . 23
   7.  Additional Work  . . . . . . . . . . . . . . . . . . . . . . . 24
   8.  Security Considerations  . . . . . . . . . . . . . . . . . . . 24
   9.  Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . 24
   10. Informative References . . . . . . . . . . . . . . . . . . . . 25
1. Introduction
1. はじめに

Spam, defined as the transmission of bulk unsolicited email, has been a plague on the Internet email system. 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. Consequently, it can be just as much of a target for spam as email. To deal with this, solutions need to be defined and recommendations put into place for dealing with spam as soon as possible.


This document serves to meet those goals by defining the problem space more concretely, analyzing the applicability of solutions used in the email space, identifying protocol mechanisms that have been defined for SIP that can help the problem, and making recommendations for implementors.


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:

電子メールでのスパム問題をよく理解され、そして我々はさらに、ここでそれについて詳しく説明する試みをしません。質問は、しかし、スパムの意味はSIPに適用されたときに何ですか? SIPは、機能の広い範囲をカバーするため、3つの関連が異なる症状があるように思われます。

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. This is often called SPam over Ip Telephony, or SPIT.


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 that 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. This is often called SPam over Instant Messaging, or SPIM.

IMスパム:スパムのこのタイプは、電子メールと同様です。それは、その内容スパマーが伝えるしようとしているメッセージが含まれているインスタントメッセージのバルク迷惑セットとして定義されます。 IMスパムが最も自然にSIPメッセージ[3]要求を使用して送信されます。しかし、コンテンツは自動的にユーザーのディスプレイに表示されるようになり、他の要求にも十分です。それは大きな件名ヘッダを持つINVITE要求を含めることができます(件名は時々、ユーザーにレンダリングされるので)、またはテキストまたはHTML機関とのINVITE要求。これは、多くの場合、インスタントメッセージング、またはSPIMを超えるスパムと呼ばれています。

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 [6]), 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. This is occasionally called SPam over Presence Protocol, or SPPP.

プレゼンススパム:スパムのこのタイプは、IMスパムに似ています。これは、順番に、ユーザの「バディリスト」または「ホワイトリスト」を取得する試みで、(すなわち、[6]プレゼンスイベントパッケージのための[4] SUBSCRIBE要求)プレゼンス要求のバルク迷惑セットとして定義されそれらをIM送信または通信の他の形態を開始します。これは、時折プレゼンスプロトコル、またはSPPP超えるスパムと呼ばれています。

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 User Agent Server (UAS). No content is delivered to the user, and they are not consulted.

スパマーが送信する可能性のある他の多くのSIPメッセージがあります。しかし、他のもののほとんどは、ユーザーに配信されるコンテンツにはなりません、また彼らは、ユーザからの入力を求めます。むしろ、彼らはオートマトンによって回答されています。 OPTIONSはこの良い例です。それはユーザエージェントサーバ(UAS)によって自動的に応答しているのでOPTIONS要求を送信におけるスパマーのために少し値は、あります。いかなるコンテンツがユーザーに配信されていない、と彼らは参照されません。

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
2.1. コールスパム

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 that can perform telemarketer call, and in cost per call.


Both of these costs are substantially reduced by SIP. A SIP call spam application is easy to write. It is just a SIP User Agent 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 software components. It can run on a low-end PC and requires no special expertise to execute.

これらのコストの両方が、実質的にSIPによって減少しています。 SIPコールのスパムアプリケーションは書きやすいです。それはちょうど、並行して、多数のコールを開始し、SIPユーザエージェントです。通話が接続されている場合、スパムアプリケーションはACKを生成し、録音アナウンスを再生するに進み、それが通話を終了します。この種のアプリケーションは、既製のソフトウェアコンポーネントを容易に入手可能な(実際、フリー)を使用して、完全にソフトウェアに内蔵することができます。これは、ローエンドのPC上で実行し、実行するための特別な専門知識を必要とすることはできません。

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 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.

コールあたりのコストも大幅に低減されます。通常の住宅の電話回線は一つだけコールが一度に配置することができます。追加の行が必要な場合、ユーザーは、より高価な接続を購入する必要があります。典型的には、T1またはT3は、大容量のテレマーケティングサービスのために必要とされるであろう。アクセスのようなものは非常に高価でも平均的なユーザーの手の届かないところです。 T1回線は約米国月額$ 250との通話のために毎分約1.5セントです。のみ(この場合のように)アウトバウンドコールに使用するT1回線は、プロバイダが支払うと受け取ることにより、相互の着信料金にしても、着信トランクよりも高価です。

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 10 seconds 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 10 seconds of content.

コール試行率、および進行中であることができ、同時に成功したコール数:容量には2つの側面があります。 T1は、最大で、スパマーを許可する24回の同時コール、および各コール試行、毎秒約2.4コールの試行のために約10秒を仮定します。大量の通話では、毎分率がはるかにT1のための月額料金を超えています。その結果、コンテンツの10秒を想定し、各成功したスパム配信のための25万microcentsのコストです。

With SIP, this cost is much reduced. Consider a spammer using a typical broadband Internet connection that provides 500 Kbps of upstream bandwidth. Initiating a call requires just a single INVITE message. Assuming, for simplicity's sake, that this is 1 KB, a 500 Kbps 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 5.3 Kbps), this requires approximately 16 Kbps after RTP, UDP, and IP overheads. With 500 Kbps upstream bandwidth, this means as many as 31 simultaneous calls can be in progress. With 10 seconds of content per call, that allows for 3.1 successful call attempts per second. If broadband access is around $50/month, the cost per successful voice spam is about 6.22 microcents each. This assumes that calls can be made 24 hours a day, 30 days a month, which may or may not be the case.

SIPでは、このコストが大幅に削減されます。アップストリーム帯域幅の500 Kbpsのを提供する典型的なブロードバンドインターネット接続を使用して、スパマーを考えます。通話を開始すると、単に1つのINVITEメッセージが必要です。これは1キロバイト、500 Kbpsの上流DSLやケーブルモデム接続は毎秒約62コールの試行を許可することで、簡単のため、と仮定。成功したコールは、受信機にメッセージを送信するために十分な帯域幅が必要です。低圧縮コーデック(たとえば、5.3 kbpsでG.723.1)を仮定すると、これはRTP、UDP、およびIPのオーバーヘッド後の約16 Kbpsのが必要です。 500 Kbpsのアップストリーム帯域幅を使用すると、これは、多くの31として同時コールが進行中であることを意味することができます。コールあたりのコンテンツの10秒で、それは毎秒3.1成功したコールの試行が可能になります。ブロードバンドアクセスは約$ 50 /月の場合は、成功した音声スパムあたりのコストを約6.22 microcentsそれぞれです。これは、呼び出しが1日24時間、30日または場合であってもなくてもよい月を行うことができることを前提としています。

These figures indicate that SIP call spam is roughly four orders of magnitude cheaper to send than traditional circuit-based telemarketer calls. This low cost is certainly going to be very attractive to spammers. Indeed, many spammers utilize computational and bandwidth resources provided by others, by infecting their machines with viruses that turn them into "zombies" that can be used to generate spam. This can reduce the cost of call spam to nearly zero.


Even ignoring the zombie issue, this reduction in cost is even more amplified for international calls. Currently, there are few telemarketing calls across international borders, largely due to the large cost of making international calls. This is one of the reasons why the "do not call list", a United States national list of numbers that telemarketers cannot call -- has been effective. The law only affects U.S. companies, but since most telemarketing calls are domestic, it has been effective. Unfortunately (and fortunately), the IP network provides no boundaries of these sorts, and calls to any SIP URI are possible from anywhere in the world. This will allow for international spam at a significantly reduced cost.

でもゾンビの問題を無視して、コストのこの減少は、さらに多くの国際通話のために増幅されます。現在は、主に国際電話をかけるの大きなコストに国境を越えて、いくつかのセールス電話は、あります。有効であった - これは、「呼び出すことはありませんリスト」、勧誘電話を呼び出すことはできません数字の米国国家のリストが理由の一つです。法律は唯一の米国企業に影響を与えますが、ほとんどのセールス電話は、国内なので、それが有効でした。残念ながら(と幸い)、IPネットワークは、これらの種類のない境界を提供しないと、任意のSIP URIへの呼び出しは、世界中のどこからでも可能です。これは、大幅に低コストで国際的なスパムが可能になります。

International spam is likely to be even more annoying than national spam, since it may arrive in languages that the recipient doesn't even speak.


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 Voice over IP (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, 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.


It is useful to compare these figures with email. VoIP can deliver approximately 3.1 successful call attempts per second. Email spam can, of course, deliver more. Assuming 1 KB per email, and an upstream link of 500 Kbps, a spammer can generate 62.5 messages per second. This number goes down with larger messages of course. Interestingly, spam filters delete large numbers of these mails, so the cost per viewed message is likely to be much higher. In that sense, call spam is much more attractive, since its content is much more likely to be examined by a user if a call attempt is successful.

電子メールでこれらの数字を比較するのに便利です。 VoIPは毎秒約3.1成功したコールの試行を提供することができます。スパムメールは、当然のことながら、より多くを提供することができます。 1メールあたりのKB、および500 Kbpsの上流リンクと仮定すると、スパム送信者は、毎秒62.5メッセージを生成することができます。この数はもちろんの大きなメッセージにダウン。興味深いことに、スパムフィルタは、これらのメールを大量に削除するので、表示されているメッセージあたりのコストがはるかに高くなる可能性があります。その意味で、その内容ははるかコールの試みが成功した場合、ユーザーによって検査される可能性があるため、スパムは、はるかに魅力的であると呼びます。

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 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.

スパムのコストの別の部分は、アドレスを収集しています。スパマーは、時間をかけて、スパム指向する電子メールアドレス、user @ domain形式のそれぞれの巨大なリストを、築いてきました。 SIPは、それはおそらく電子メールアドレスを簡単に有効なSIPアドレスに変換することができますことを作り、対処するのと同じ形式を使用しています。電話番号は、有効なSIPアドレスを表します。終了プロバイダと協調して、SIPを指示することができますスパマーは、従来のPSTNデバイスで呼び出します。彼らは彼らのウェブスイープを行うと、電子メールスパマーはまた、電話番号を収集してきたかどうかは明らかではないが、そうするだろう難しいことではありません。さらに、電子メールアドレスとは異なり、電話番号はかなり密に充填された有限のアドレス空間と一つです。その結果、電話番号を順番に行くのはかなり高いヒット率を生成する可能性があります。このように、スパマーはSIPを大量に取得するためのコストが比較的低いようにそれはそうと、そのスパムを向けることができるために対処しています。

2.2. IM Spam
2.2. IMスパム

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, that is 62.5 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, most popular IM systems employ white lists, which only allow IM 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.

IMスパムは、スパムを展開して生成するためのコストの面で、非常に多くの電子メールのようなものです。仮定すると、引数のために、1キロバイトメッセージが送信されると、アップストリーム帯域幅の500 Kbpsのは、それは、毎秒62.5メッセージです。 $ 50 /月で、その結果は、メッセージごとに0.31 microcentsです。これは、音声スパム未満が、実質的に少ないではありません。コストは、電子メールスパムに匹敵すると考えられます。しかし、IMは、はるかに侵入電子メールを超えています。今日のシステムでは、IMSが自動的にポップアップし、利用者に自分自身を提示します。メールは、当然のことながら、意図的に選択して表示する必要があります。しかし、最も人気のIMシステムは、送信者がホワイトリスト上にある場合のみ、IMが配信されるように可能にする、ホワイトリストを採用しています。このように、IMスパムが有用であろうかどうかは、ネットワークが開かれるようシステムの性質に多くを依存しているようです。彼らは普遍的にホワイトリストへのアクセスに配備されている場合は、IMスパムの値が低くなる可能性があります。

It is important to point out that there are two different types of IM systems: page mode and session mode. Page mode IM systems work much like email, with each IM being sent as a separate message. In session mode IM, there is signaling in advance of communication to establish a session, and then IMs are exchanged, perhaps point-to-point, as part of the session. The modality impacts the types of spam techniques that can be applied. Techniques for email can be applied identically to page mode IM, but session mode IM is more like telephony, and many techniques (such as content filtering) are harder to apply.


2.3. Presence Spam
2.3. プレゼンススパム

As defined above, presence spam is the generation of bulk unsolicited SUBSCRIBE messages. The cost of this is within a small constant factor of IM spam so the same cost estimates can be used here. What would be the effect of such spam? Most presence systems provide some kind of consent framework. A watcher that has not been granted permission to see the user's presence will not gain access to their presence. However, the presence request is usually noted and conveyed to the user, allowing them to approve or deny the request. In SIP, this is done using the watcherinfo event package [7]. This package allows a user to learn the identity of the watcher, in order to make an authorization decision.

上記で定義したように、プレゼンススパムが大量の迷惑SUBSCRIBEメッセージの生成です。同じコストの見積もりは、ここで使用することができますので、このコストは、IMスパムの小さな定数倍以内です。こうしたスパムの影響は何でしょうか?ほとんどのプレゼンスシステムは同意フレームワークのいくつかの種類を提供しています。その存在へのアクセスを獲得しません、ユーザーのプレゼンスを表示する権限を付与されていませんウォッチャー。しかし、プレゼンス要求は通常、注目されると、それらは要求を承認または拒否することができ、ユーザに伝えます。 SIPにおいては、これはwatcherinfoイベントパッケージを使用して行われる[7]。このパッケージには、ユーザーが承認決定を行うために、ウォッチャーのアイデンティティを学ぶことができます。

Interestingly, this provides a vehicle for conveying information to a user. By generating SUBSCRIBE requests from identities such as, brief messages can be conveyed to the user, even though the sender does not have, and never will receive, permission to access presence. As such, presence spam can be viewed as a form of IM spam, where the amount of content to be conveyed is limited. The limit is equal to the amount of information generated by the watcher that gets conveyed to the user through the permission system.

興味深いことに、これは、ユーザに情報を伝達するための手段を提供します。 SIPなどのアイデンティティからの要求SUBSCRIBE生成することにより:please-buy-my-product@spam.example.comを、簡潔なメッセージが送信者が持っていないにも関わらず、利用者に伝えることができませんし、決して、存在へのアクセス許可を受け取ります。このように、プレゼンス・スパムが搬送されるコンテンツの量が限られているIMスパム、の形態と見なすことができます。制限は、許可システムを介してユーザに伝えますウォッチャによって生成される情報の量に等しいです。

This type of spam also shows up in consent frameworks used to prevent call spam, as discussed in Section 3.4.


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
3.1. コンテンツフィルタリング

The most common form of spam protection used in email is based on content filtering. 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, while successful for email spam, is 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 research.

残念ながら、スパムフィルタリングのこのタイプは、電子メールのスパムのために成功しながら、コールスパムのための完全に役に立たないです。 2つの理由があります。まず、ユーザがコールに応答する場合には、コールがすでに確立されていると、コンテンツが配信される前に、ユーザーは注意を払っています。ユーザーがそれを見る前にスパムを分析することはできません。ユーザがそれにアクセスする前に、コンテンツ(例えば、ボイスメールで)格納されている場合に、第2の、コンテンツを記録したオーディオまたはビデオの形態であろう。音声・映像認識技術は、コンテンツを分析し、それがスパムであるかどうかを判断するために十分である可能性が高いではありません。システムは、このような分析を行うために、記録上の音声認識を行うためにしようとした場合、スパマーは認識システムをオフにスローされますすべてがバックグラウンドノイズ、貧しい文法、および多様なアクセント、と電話をかけることのために実際に、それは簡単だろう。映像認識を行うのはさらに困難であり、主な研究分野のまま。

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
3.2. ブラックリスト

Black listing is an approach whereby the spam filter maintains a list of addresses that identify spammers. These addresses include both usernames ( and entire domains ( 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.


As a result, as long as identities are easy to manufacture, or zombies are used, black lists will have limited effectiveness for email.


Blacklists are also likely to be ineffective for SIP spam. Mechanisms for inter-domain authenticated identity for email and SIP are discussed in Section 4 and Section 5. Assuming these mechanisms are used and enabled in inter-domain communications, it becomes difficult to forge sender addresses. However, it still remains cheap to obtain a nearly infinite supply of addresses.


3.3. White Lists
3.3. ホワイトリスト

White lists are the opposite of black lists. It is a list of valid senders that a user is willing to accept email from. Unlike black lists, a spammer cannot change identities to get around the white list. White lists are susceptible to address spoofing, but a strong identity authentication mechanism can prevent that problem. As a result, the combination of white lists and strong identity, as described in Section 4.2 and Section 5, are a good form of defense against spam.

ホワイトリストは、ブラックリストの逆です。これは、ユーザーからのメールを受け入れて喜んで有効な送信者のリストです。ブラックリストとは異なり、スパマーは、ホワイトリストを回避するためのIDを変更することはできません。ホワイトリストは、なりすましに対処するために影響を受けやすいが、強力なアイデンティティ認証メカニズムは、その問題を防ぐことができます。 4.2節と第5節で説明したようにその結果、ホワイトリストおよび強力なアイデンティティーの組み合わせは、スパムに対する防御の良い形です。

However, they are not a complete solution, since they would prohibit a user from ever being able to receive email from someone who was not explicitly put on the white list. As a result, white lists require a solution to the "introduction problem" - how to meet someone for the first time, and decide whether they should be placed in the white list. In addition to the introduction problem, white lists demand time from the user to manage.

彼らはこれまで明示的にホワイトリストに入れていなかった誰かからのメールを受信することができることからユーザーを禁止するので、しかし、彼らは、完全なソリューションではありません。その結果、ホワイトリストは、「導入の問題」の解決策を必要と - 初めて誰かに会うと、彼らはホワイトリストに置かれるべきかどうかを決定する方法。導入の問題に加えて、ホワイトリストは、管理するために、ユーザからの時間を必要としています。

In IM systems, white lists have proven exceptionally useful at preventing spam. This is due, in no small part, to the fact that the white list exists naturally in the form of the buddy list. Users don't have to manage this list just for the purposes of spam prevention; it provides general utility, and assists in spam prevention for free. Many popular IM systems also have strong identity mechanisms since they do not allow communications with IM systems in other administrative domains. The introduction problem in these systems is solved with a consent framework, described below.


The success of white lists in IM systems has applicability to SIP as well. This is because SIP also provides a buddy list concept and has an advanced presence system as part of its specifications. The introduction problem remains. In email, techniques like Turing tests have been employed to address the introduction problem. Turing tests are considered further in the sections below. As with email, a technique for solving the introduction problem would need to be applied in conjunction with a white list.

IMシステムにおけるホワイトリストの成功は、同様にSIPに適用可能です。 SIPはまた、バディリストの概念を提供し、その仕様の一部として、先進的なプレゼンスシステムを持っているためです。導入の問題が残っています。電子メールでは、チューリング・テストのような技術は、導入の問題に対処するために採用されています。チューリングテストは、以下のセクションでさらに考えられています。電子メールと同じように、導入の問題点を解決するための技術は、ホワイトリストと併せて適用する必要があるであろう。

If a user's computer is compromised and used a zombie, that computer can usually be used to send spam to anyone that has put the user on their white list.


3.4. Consent-Based Communications
3.4. 同意ベースの通信

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 had attempted communications. User B can then authorize or reject user A.


These kinds of consent-based systems are used widely in presence and IM. Since most of today's popular IM systems only allow communications within a single administrative domain, sender identities can be authenticated. Email often uses similar consent-based systems for mailing lists. They use a form of authentication based on sending cookies to an email address to verify that a user can receive mail at that address.


This kind of consent-based communications has been standardized in SIP for presence, using the watcher information event package [7] and data format [8], 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.


A consent framework has also been developed that is applicable to other forms of SIP communications [12]. However, this framework focuses on authorizing the addition of users to "mailing lists", known as exploders in SIP terminology. Though spammers typically use such exploder functions, presumably one run by a spammer would not use this technique. Consequently, this consent framework is not directly applicable to the spam problem. It is, however, useful as a tool for managing a white list. Through the PUBLISH mechanism, it allows a user to upload a permission document [13] that indicates that they will only accept incoming calls from a particular sender.

同意フレームワークはまた、SIP通信[12]の他の形態に適用可能であることが開発されています。しかし、このフレームワークは、SIP用語で発破として知られているユーザーには、「メーリングリスト」の追加を許可に焦点を当てています。スパマーは通常、エクスプローダ機能を使用していますが、おそらくスパマーずつ実行は、この技術を使用することはありません。したがって、この同意フレームワークは、スパム問題に直接適用することはできません。それは、しかし、ホワイトリストを管理するためのツールとして有用です。 PUBLISH機構を介して、ユーザは、彼らが唯一の特定の送信者からの着信を受け入れることを示し許可書[13]をアップロードすることができます。

Can a consent framework, like the ones used for presence, help solve call spam? 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. Those requests for communications don't convey much useful content to the user, but they can convey some. At the very least, they will convey the identity of the requester. The user part of the SIP URI allows for limited free form text, and thus could be used to convey brief messages. One can imagine receiving consent requests with identities like "", for example. Fortunately, it is possible to apply traditional content filtering systems to the header fields in the SIP messages, thus reducing these kinds of consent request attacks.

同意フレームワークは、存在のために使用されるもののように、コール・スパムの解決に役立つことはできますか?一見すると、多くのことを助けるように思われます。しかし、それだけでスパムの性質を変更する場合があります。代わりに、コールスパムやIMスパムの形で、コンテンツに煩わされるのは、ユーザーが同意要求に悩まされています。ユーザの「通信の受信トレイ」が代わりにユーザーの多様からの通信の要求を満たしている可能性があります。通信のためのこれらの要求は、ユーザーに多くの有用な内容を伝えていないが、彼らはいくつかを伝えることができます。少なくとも、彼らが依頼者の身元を伝えます。 SIP URIのユーザ部分は、限られた自由形式のテキストを可能にし、したがって、簡単なメッセージを伝えるために使用することができます。例えば、:一つは「please-buy-my-product-at-this-website@spam.example.com一口」のようなアイデンティティと同意のリクエストを受けて想像することができます。幸いなことに、このように同意要求攻撃のこれらの種類を減らし、SIPメッセージのヘッダーフィールドに、伝統的なコンテンツ・フィルタリング・システムを適用することが可能です。

In order for the spammer to convey more extensive content to the user, the user must explicitly accept the request, and only then can the spammer convey the full 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, the value in sending spam is reduced, and perhaps it will cease for those spam cases where consent is not given to spammers.


As such, the real question is whether or not the consent system would 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 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 ensure that 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. It may even be possible that an automated system could do some form of content analysis on this initial short message. However, this 200 words of text may be enough for a spammer to convey their message, in much the same way they might convey it in the user part of the SIP URI.

具体的には、ボブは、彼は、ユーザーがより多くの権限が適切であるかどうかを判断できるように、自分自身を識別するために使用することができ、単一のIM、テキストのこれ以上の200以上の単語を送信する権限を付与することができます。それも、自動化されたシステムは、この最初のショートメッセージの内容分析のいくつかのフォームを行うことができることも可能です。スパマーが多くので、彼らはSIP URIのユーザ部分でそれを伝える可能性があると同じように自分のメッセージを伝えるためにためしかし、テキストのこの200本の言葉は十分かもしれません。

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. Reputation Systems
3.5. レピュテーションシステム

A reputation system is also used in conjunction with white or black lists. Assume that user A is not on user B's white list, and A attempts to contact user B. If a consent-based system is used, B is prompted to consent to communications from A, and along with the consent, a reputation score might be displayed in order to help B decide whether or not they should accept communications from A.


Traditionally, reputation systems are implemented in highly centralized messaging architectures; the most widespread reputation systems in messaging today have been deployed by monolithic instant messaging providers (though many Web sites with a high degree of interactivity employ very similar concepts of reputation). Reputation is calculated based on user feedback. For example, a button on the user interface of the messaging client might empower users to inform the system that a particular user is abusive. Of course, the input of any single user has to be insufficient to ruin one's reputation, but consistent negative feedback would give the abusive user a negative reputation score.

伝統的に、評判システムは、高度に集中メッセージングアーキテクチャで実装されています。 (対話度の高い多くのWebサイトが評判の非常によく似たコンセプトを採用しても)メッセージングで最も広く普及しているレピュテーションシステム今日は、モノリシックインスタント・メッセージング・プロバイダーによって展開されています。評判は、ユーザーからのフィードバックに基づいて計算されます。例えば、メッセージングクライアントのユーザーインターフェース上のボタンは、特定のユーザが虐待であるシステムに通知するために、ユーザーに権限を与えるかもしれません。もちろん、任意の単一のユーザーの入力が1の評判を台無しにするには不十分である必要がありますが、一貫性の負のフィードバックは、虐待的なユーザーに負のレピュテーションスコアを与えるだろう。

Reputation systems have been successful in systems where centralization of resources (user identities, authentication, etc.) and monolithic control dominate. Examples of these include the large instant messaging providers that run IM systems that do not exchange messages with other administrative domains. That control, first of all, provides a relatively strong identity assertion for users (since all users trust a common provider, and the common provider is the arbiter of authentication and identity). Secondly, it provides a single place where reputation can be managed.

レピュテーションシステムは資源の集中(ユーザーID、認証など)と、モノリシック制御が支配システムで成功しています。これらの例は、他の管理ドメインとメッセージを交換していないIMシステムを実行する大規模なインスタント・メッセージング・プロバイダーが含まれます。 (すべてのユーザが共通のプロバイダを信頼するので、共通のプロバイダは、認証と同一のアービタである)まずその制御は、ユーザのために比較的強いIDアサーションを提供します。第二に、それが評判を管理することができ、単一の場所を提供します。

Reputation systems based on negative reputation scores suffer from many of the same problems as black lists, since effectively the consequence of having a negative reputation is that you are blacklisted. If identities are very easy to acquire, a user with a negative reputation will simply acquire a new identity. Moreover, negative reputation is generated by tattling, which requires users to be annoyed enough to click the warning button -- a process that can be abused. In some reputation systems, "reputation mafias" consisting of large numbers of users routinely bully or extort victims by threatening collectively to give victims a negative reputation.

負の評判を持っていることの効果的な結果は、あなたがブラックリストに載っているということであるので、負のレピュテーションスコアに基づいてレピュテーションシステムは、ブラックリストと同じ問題の多くに苦しみます。アイデンティティが取得するのは非常に簡単であれば、負の評判を持つユーザーは、単純に新しいアイデンティティを取得します。悪用される可能性がプロセス - また、負の評判は警告]ボタンをクリックして、十分に悩まされるようにユーザーが必要とする、tattlingによって生成されます。いくつかのレピュテーションシステムでは、多数のユーザーから成る「評判のマフィアは」日常の犠牲者に否定的な評判を与えることを総称して脅しによって、被害者をいじめたり強要します。

Reputation systems based on positive reputation, where users praise each other for being good, rather than tattling on each other for being bad, have some similar drawbacks. Collectives of spammers, or just one spammer who acquires a large number identities, could praise one another in order to create an artificial positive reputation. Users similarly have to overcome the inertia required to press the "praise" button. Unlike negative reputation systems, however, positive reputation is not circumvented when users acquire a new identity, since basing authorization decisions on positive reputation is essentially a form of white listing.


So, while positive reputation systems are superior to negative reputation systems, they are far from perfect. Intriguingly, though, combining presence-based systems with reputation systems leads to an interesting fusion. The "buddy-list" concept of presence is, in effect, a white list - and one can infer that the users on one's buddy list are people whom you are "praising". This eliminates the problem of user inertia in the use of the "praise" button, and automates the initial establishment of reputation.

ポジティブ評判システムは、負のレピュテーションシステムより優れている一方、そう、彼らは完璧にはほど遠いです。興味深いことに、しかし、レピュテーションシステムでプレゼンスベースのシステムを組み合わせることで、興味深い融合につながります。プレゼンスの「バディリスト」のコンセプトは、実際には、ホワイトリストである - そして一つは自分のバディリスト上のユーザーは、あなたが「賛美」している人であることを推測することができます。これは、「賞賛」ボタンを使用することで、ユーザの慣性の問題を解消し、評判の最初の確立を自動化します。

And of course, your buddies in turn have buddies. Collectively, you and your buddies (and their buddies, and so on) constitute a social network of reputation. If there were a way to leverage this social network, it would eliminate the need for centralization of the reputation system. Your perception of a particular user's reputation might be dependent on your relationship to them in the social network: are they one buddy removed (strong reputation), four buddies removed (weaker reputation), three buddies removed but connected to you through several of your buddies, etc. This web of trust furthermore would have the very desirable property that circles of spammers adding one another to their own buddy lists would not affect your perception of their reputation unless their circle linked to your own social network.


If a users machine is compromised and turned into a zombie, this allows SPAM to be sent and may impact their reputation in a negative way. Once their reputation decreases, it becomes extremely difficult to reestablish a positive reputation.


3.6. Address Obfuscation
3.6. アドレス難読化

Spammers build up their spam lists by gathering email addresses from Web sites and other public sources of information. One way to minimize spam is to make your address difficult or impossible to gather. Spam bots typically look for text in pages of the form "user@domain", and assume that anything of that form is an email address. To hide from such spam bots, many Web sites have recently begun placing email addresses in an obfuscated form, usable to humans but difficult for an automata to read as an email address. Examples include forms such as, "user at example dot com" or "j d r o s e n a t e x a m p l e d o t c o m".

スパマーは、Webサイトや情報の他の公共の情報源からの電子メールアドレスを収集することによって、そのスパムリストを構築します。スパムを最小限にする一つの方法は、収集するあなたのアドレスが困難または不可能にすることです。スパムボットは、通常はフォーム「ユーザー@ドメイン」のページ内のテキストを探し、そのフォームの何かが電子メールアドレスであることを前提としています。こうしたスパムボットから非表示にするには、多くのWebサイトでは、最近のメールアドレスとして読み込むためのオートマトンのために、ヒトに使用できるが、困難な難読化形式で電子メールアドレスを置く始めています。例としては、 "COMドット例において、ユーザ" または "J d個のR O S E N T EはE、D、O、T、C、O M MのP Lを×"。ような形態を含みます

These techniques are equally applicable to prevention of SIP spam, and are likely to be as equally effective or ineffective in its prevention.


It is worth mentioning that the source of addresses need not be a Web site - any publicly accessible service containing addresses will suffice. As a result, ENUM [9] has been cited as a potential gold mine for spammers. It would allow a spammer to collect SIP and other URIs by traversing the tree in and mining it for data. This problem is mitigated in part if only number prefixes, as opposed to actual numbers, appear in the DNS. Even in that case, however, it provides a technique for a spammer to learn which phone numbers are reachable through cheaper direct SIP connectivity.

アドレスを含む任意の公的にアクセス可能なサービスは十分でしょう - アドレスのソースがWebサイトである必要はないことを言及する価値があります。結果として、[9] ENUMは、スパマーのための潜在的な金鉱として引用されています。これは、スパマーがe164.arpaにツリーをトラバースし、データのためにそれをマイニングすることにより、SIPおよび他のURIを収集できるようになります。唯一の番号のプレフィックスは、実際の数値とは反対に、DNSに表示されている場合、この問題は、一部に緩和されます。その場合であっても、しかし、それは安く、直接SIP接続を介して到達可能である電話番号を学ぶためのスパマーのための技術を提供します。

3.7. Limited-Use Addresses
3.7. 限定使用アドレス

A related technique to address obfuscation is limited-use addresses. In this technique, a user has a large number of email addresses at their disposal, each of which has constraints on its applicability. A limited-use address can be time-bound, so that it expires after a fixed period. Or, a different email address can be given to each correspondent. When spam arrives from that correspondent, the limited-use address they were given is terminated. In another variation, the same limited-use address is given to multiple users that share some property; for example, all work colleagues, all coworkers from different companies, all retailers, and so on. Should spam begin arriving on one of the addresses, it is invalidated, preventing communications from anyone else that received the limited use address.


This technique is equally applicable to SIP. One of the drawbacks of the approach is that it can make it hard for people to reach you; if an email address you hand out to a friend becomes spammed, changing it requires you to inform your friend of the new address. SIP can help solve this problem in part, by making use of presence [6].

この手法は、SIPにも同様に適用可能です。アプローチの欠点の1つは、それが難しい人々があなたに到達するために作ることができるということです。あなたは友人に配るのメールアドレスがスパムになった場合、それを変更すると、新しいアドレスのあなたの友人を通知する必要があります。 SIPは、プレゼンス[6]を利用して、部分的にこの問題を解決することができます。

Instead of handing out your email address to your friends, you would hand out your presence URI. When a friend wants to send you an email, they subscribe to your presence (indeed, they are likely to be continuously subscribed from a buddy list application). The presence data can include an email address where you can be reached. This email address can be obfuscated and be of single use, different for each buddy who requests your presence. They can also be constantly changed, as these changes are pushed directly to your buddies. In a sense, the buddy list represents an automatically updated address book, and would therefore eliminate the problem.


Another approach is to give a different address to each and every correspondent, so that it is never necessary to tell a "good" user that an address needs to be changed. This is an extreme form of limited-use addresses, which can be called a single-use address. Mechanisms are available in SIP for the generation of [16] an infinite supply of single use addresses. However, the hard part remains a useful mechanism for distribution and management of those addresses.


3.8. Turing Tests
3.8. チューリング・テスト

In email, Turing tests are mechanisms whereby the sender of the message is given some kind of puzzle or challenge, which only a human can answer (since Turing tests rely on video or audio puzzles, they sometimes cannot be solved by individuals with handicaps). These tests are also known as captchas (Completely Automated Public Turing test to tell Computers and Humans Apart). 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. The tests need to be designed such that automata cannot easily perform the image recognition needed to extract the word or number sequence, but a human user usually can. Designing such tests is not easy, since ongoing advances in image processing and artificial intelligence continually raise the bar. Consequently, the effectiveness of captchas are tied to whether spammers can come up with or obtain algorithms for automatically solving them.


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.


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 Interactive Voice Response (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 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 white list.

呼スパムは、通常、人間がもう一方の端にあることを確認するために使用することができ、画像やその他のコンテンツの転送を伴わないため、チューリングテストは、直接ではなくが、同様にスパムを呼び出すために適用することができます。呼び出しのほとんどが音声であれば、技術は音声に適応させる必要があります。これを行うのはそれほど難しくはありません。ここでそれを行うことができる方法です。ユーザAは、ユーザBを呼び出し、ユーザBの白または黒のリストに載っていません。ユーザーAは、対話型音声応答(IVR)システムに転送されます。 IVRシステムは、彼らは一連の数字(彼らの言う5)を聞くしようとしているユーザーに伝え、そして、彼らはキーパッド上のこれらの数字を入力する必要があること。背景音楽が再生されている間、IVRシステムは、それが困難なメディアに適用される自動化された音声認識システムのために作る、番号を読み出します。その後、ユーザは自分のキーパッドで番号を入力します。彼らが正しく入力されている場合、ユーザーはホワイトリストに追加されます。

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 [14]. 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 [15]), but also including Web browsers, voice recognition, and so on. The framework allows the application to determine the media capabilities of the device (or user, in cases where they are handicapped) and interact with them appropriately.


In the case of voice, the Turing test would need to be made to run in the language of the caller. This is possible in SIP, using the Accept-Language header field, though this is not widely used at the moment, and meant for languages of SIP message components, not the media streams.


The primary problem with the voice 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 60 cents per hour, and assuming a Turing test of a 30-second duration, this is about 0.50 cents per test and thus 0.50 cents per message to send an IM spam. Lower labor rates would reduce this further; the number quoted here is based on real online bids in September of 2006 made for actual work of this type.


As an alternative to paying cheap workers to take the tests, the tests can be taken by human users that are tricked into completing the tests in order to gain access to what they believe is a legitimate resource. This was done by a spambot that posted the tests on a pornography site, and required users to complete the tests in order to gain access to content.


Due to these limitations, Turing tests may never completely solve the problem.


3.9. Computational Puzzles
3.9. 計算パズル

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.


One of the problems with the technique 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 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 [26]. It seems that there is less variety in the CPU/memory bandwidth across devices, roughly a single order of magnitude.

技術の問題点の一つは、合法的に通信する可能性のあるさまざまなクライアントの計算能力には大きなばらつきがあるということです。ハイエンドPCが5 GHz帯に近づく一方で、ローエンドの携帯電話上のCPUの速度は、約50 MHzです。これは、大きさの差のほぼ二桁を表します。テストが携帯電話が実行するために合理的であるように設計される場合、ハイエンドマシン上スパマーに対して実行する二桁安価です。ちょうどCPU [26]とは対照的に最近の研究では、CPU /メモリの帯域幅に挑戦計算パズルを明確にすることに集中しました。デバイス間でCPU /メモリ帯域幅が少なく、様々な大きさの約単一の注文があるようです。

Recent work [28] suggests that, due to the ability of spammers to use virus-infected machines (also known as zombies) to generate the spam, the amount of computational power available to the spammers is substantial, and it may be impossible to have them compute a puzzle that is sufficiently hard that will not also block normal emails. If combined with white listing, computational puzzles would only be utilized for new communications partners. Of course, if the partner on the white list is a zombie, spam will come from that source. The frequency of communications with new partners is arguably higher for email than for multimedia, and thus the computational puzzle techniques may be more effective for SIP than for email in dealing with the introduction problem.


These techniques are an active area of research right now, and any results for email are likely to be usable for SIP.


3.10. Payments at Risk
3.10. リスクの支払い

This approach has been proposed for email [27]. When user A sends email 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.

このアプローチは、電子メール[27]が提案されています。ユーザAは、ユーザBの口座にお金を少量(例えば、1ドル)、ユーザBにユーザAの預金を電子メールを送信するとき。ユーザBはメッセージがスパムでないことを決定した場合、ユーザーBの払い戻しバックユーザAへのメッセージがスパムである場合は、このお金は、ユーザBは、お金を保持します。 、AからBへの転送、およびバックAにBからの転送最初の転送は、メッセージが複数のメッセージを横切る「保留支払い」の再使用を回避するために受信される前に発生することがあります。この技術は、完了するために2つのトランザクションを必要としますその解決策の有用性を排除するであろう。もう一つは、メッセージがスパムでないと発見された場合に発生する必要があります。

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 infrastructure.


This technique has the potential to make it arbitrarily 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, 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 0.75 cents and deliver 4.25 cents. If the sender is allowed, the recipient returns 4.25 cents, the provider takes 0.64 cents, and returns 3.6 cents. This costs the sender 0.65 cents on each transaction, if it was legitimate. If there are ten new recipients per day, that is US $1.95 per month, which is relatively inexpensive.

この技術は、任意の高価なあらゆる種類のスパムを送信できるようにする可能性を秘めています。しかし、それはインターネット上で安価な少額決済技術に依存しています。インターネットでのお支払いのための伝統的なコストは、おそらく法外だろうトランザクションあたり25セント、周りされています。しかし、最近のプロバイダは1セントと小さく、小さな取引について、取引の15%を充電するために喜んでされています。このコストは、システムのユーザによって背負っしなければならないであろう。ユーザごと肩する必要がコストが受信された未知の送信者からのメッセージの数(つまり、ホワイトリスト上の送信者ではない)に等しいです。忙しいユーザーのために、一日あたり約10個の新しい送信者を想定しています。デポジットは5セントであれば、トランザクションプロバイダは0.75セントを取り、4.25セントを提供します。送信者が許可されている場合、受信者は、プロバイダが0.64セントを取り、4.25セントを返し、3.6セントを返します。それは正当だった場合、これは、送信者各トランザクションに0.65セントの費用がかかります。一日あたり10の新しい受信者がある場合は、それが比較的安価である月額$ 1.95米です。

Assuming a micro-payment infrastructure exists, another problem with payment-at-risk is that it loses effectiveness when there are strong inequities in the value of currency between sender and recipient. For example, a poor person in a Third World country might keep the money in each mail message, regardless of whether it is spam. Similarly, a poor person might not be willing to include money in an email, even if legitimate, for fear that the recipient might keep it. If the amount of money is lowered to help handle these problems, it might become sufficiently small that spammers can just afford to spend it.


3.11. Legal Action
3.11. 法的措置

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.


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 <> inserts material in the header that, if it was inserted by a spammer without an appropriate license, would allegedly causes the spammer to violate US copyright and trademark laws, possibly reciprocal laws, and similar laws in many countries.


3.12. Circles of Trust
3.12. トラストの円

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 Transport Level Security (TLS)[22] between providers or SIP Identity [17].

この技術は、安全なドメイン間認証に依存して - それは、ドメインBは、メッセージがSIPのドメインAから受信されたことを知ることができるされ、これは容易にプロバイダまたは間の相互認証されたトランスポートレベルセキュリティ(TLS)[22]の使用によって提供されますSIPアイデンティティ[17]。

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? At what point would the network be large enough that it would be worthwhile to send spam and just pay the fine? How would the pricing be structured to allow both small and large domains alike to participate?


3.13. Centralized SIP Providers
3.13. 一元化SIPプロバイダー

This technique is a variation on the circles of trust described in Section 3.12. 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 3.10. 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 broadly 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 (compared to email!), there is some proof that this kind of arrangement can work. However, centralized architectures as these are deliberately eschewed because they put back into SIP much of the complexity and monopolistic structures that the protocol aims to eliminate.


4. Authenticated Identity in Email

Though not a form of anti-spam in and of itself, authenticated or verifiable identities are a key part of making other anti-spam mechanisms work. Many of the techniques described above are most effective when combined with a white or black list, which itself requires a strong form of identity.


In email, two types of authenticated identity have been developed - sender checks and signature-based solutions.

送信者のチェックとシグネチャベースのソリューションを - メールでは、認証されたアイデンティティの2つのタイプが開発されています。

4.1. Sender Checks
4.1. 送信者かどうかをチェック

In email, DNS resource records have been defined that will allow a domain that receives a message to verify that the sender is a valid Message Transfer Agent (MTA) for the sending domain [18] [19] [20] [21]. They don't prevent spam by themselves, but may help in preventing spoofed emails. As has been mentioned several times, a form of strong authenticated identity is key in making many other anti-spam techniques work.

電子メールでは、DNSリソースレコードは、送信者が[18] [19] [20] [21]送信元ドメインの有効なメッセージ転送エージェント(MTA)であることを確認するためのメッセージを受け取るドメインを許可するように定義されています。彼らは、自分たちで迷惑メールを防ぐことはできませんが、偽装された電子メールを防ぐのに役立つかもしれません。何度か言及したように、強力な認証されたアイデンティティの形式は、他の多くのアンチスパム技術を機能させるに重要です。

Are these techniques useful for SIP? They can be used for SIP but are not necessary. In SIP, 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. These techniques are discussed in Section of RFC 3261 [2]. In forwarding situations, the assumption no longer holds and these techniques no longer work. However, the authenticated identity mechanism for SIP, discussed in Section 5, does work in more complex network configurations and provides fairly strong assertion of identity.

これらの技術は、SIPのために有用か?彼らは、SIPのために使用されるが、必要ではないことができます。 SIPでは、相互認証とTLSは、ドメイン間使用することができます。メッセージを受信したプロバイダは、メッセージの送信者のアサートされたIDと一致していないドメインからの任意のメッセージを拒否することができます。発信者が存在する場所であり、送信ドメイン、受信ドメイン - そのようなポリシーは、任意の呼び出しにのみ2つのドメインが存在することにより、SIPの「台形」モデルで動作します。これらの技術は、RFC 3261のセクション26.3.2.2に記載されている[2]。転送状況では、仮定はもはや保持していないと、これらの技術は、もはや動作しません。しかし、第5節で議論SIPのための認証されたアイデンティティメカニズムは、より複雑なネットワーク構成で作業を行い、身元のかなり強い主張を提供します。

4.2. Signature-Based Techniques
4.2. シグネチャベースのテクニック

Domain Keys Identified Mail (DKIM) Signatures [23] (and several non-standard techniques that preceded it) provide strong identity assertions by allowing the sending domain to sign an email, and then providing mechanisms by which the receiving MTA or Mail User Agent (MUA) can validate the signature.

ドメインキー認証メール(DKIM)署名[23](及びそれに先行いくつかの非標準的な技術)、電子メールに署名する送信ドメインを可能にし、その後のメカニズムを提供することにより、強力なIDアサーションを提供することにより、受信MTAまたはメールユーザエージェント( MUA)が署名を検証することができます。

Unfortunately, when used with blacklists, this kind of authenticated identity is only as useful as the fraction of the emails that utilize it. This is partly true for white lists as well; if any unauthenticated email is accepted for an address on a white list, a spammer can spoof that address. However, a white list can be effective with limited deployment of DKIM if all the people on the white list are those whose domains are utilizing the mechanism, and the users on that white list aren't zombies.


This kind of identity mechanism is also applicable to SIP, and is in fact, exactly what is defined by SIP's authenticated identity mechanism [17].


Other signature-based approaches for email include S/MIME[24] and OpenPGP[25].

電子メールの他のシグネチャベースのアプローチは、S / MIME [24]とのOpenPGP [25]を含みます。

5. Authenticated Identity in SIP
SIP 5.認証されたID

One of the key parts of many of the solutions described above is the ability to securely identify the sender of a SIP message. SIP provides a secure solution for this problem, called SIP Identity [17], and it is important to discuss it here.

上記の解決策の多くの重要な部品の一つが確実にSIPメッセージの送信者を識別するための能力です。 SIPは、SIPアイデンティティ[17]と呼ばれるこの問題のために安全なソリューションを提供し、ここでそれを議論することが重要です。

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 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.

解決策は、各ドメインには独自のユーザを認証することによって開始します。 SIPは、HTTPコアSIP仕様の一部としてダイジェスト認証を提供し、すべてのクライアントとサーバーは、それをサポートする必要があります。確かに、ダイジェストは広くSIPのために展開されています。しかし、一人でダイジェスト最も顕著な多くの既知の脆弱性、オフライン辞書攻撃を持っています。これらの脆弱性はすべて、各クライアントがサーバへの持続的なTLS接続を維持することによって解決されます。クライアントはTLSを使用して、サーバーの身元を確認した後、TLS経由ダイジェスト交換を使用してサーバーに自分自身を認証します。また、RFC 3261で文書化されたこの技術は、非常に安全ですが、広くまだ展開ません。長期的には、このアプローチは、SIPスパムを防ぐために必要なセキュリティプロパティのために必要となります。

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 [17].


A weaker form of identity assertion is possible using the P-Asserted-Identity header field [5], but this technique requires mutual trust among all domains. Unfortunately, this becomes exponentially harder to provide as the number of interconnected domains grows. As that happens, the value of the identity assertion becomes equal to the trustworthiness of the least trustworthy domain. Since spam is a consequence of the receiving domain not being able to trust the sending domains to disallow the hosts in the sending to send spam, the P-Asserted-Identity technique becomes ineffective at exactly the same levels of interconnectedness that introduce spam.

IDアサーションの弱い形態[5] P-Asserted-Identityヘッダフィールドを使用可能であるが、この手法は、すべてのドメイン間の相互信頼関係を必要とします。残念ながら、これは、相互接続されたドメインの数の成長に合わせて提供するために、指数関数的に難しくなります。それが起こるように、IDアサーションの値は、少なくとも信頼できるドメインの信頼性と等しくなります。スパムが受信ドメインがスパムを送信するために送信してホストを許可しないように、送信ドメインを信頼することができないの結果であるので、P-アサート・アイデンティティ技術は、スパムを導入相互関連のまったく同じレベルで無効になります。

Consider the following example to help illustrate this fact. A malicious domain -- let us call them, would like to send SIP INVITE requests with false P-Asserted-Identity, indicating users outside of its own domain. finds a regional SIP provider in a small country who, due to its small size and disinterest in spam, accepts any P-Asserted-Identity from its customers without verification. This provider, in turn, connects to a larger, interconnect provider. They do ask each of their customers to verify P-Asserted-Identity but have no easy way of enforcing it. This provider, in turn, connects to everyone else. As a consequence, the domain is able to inject calls with a spoofed caller ID. This request can be directed to any recipient reachable through the network (presumably everyone due to the large size of the root provider). There is no way for a recipient to know that this particular P-Asserted-Identity came from this bad domain. As the example shows, even though the central provider's policy is good, the overall effectiveness of P-Asserted-Identity is still only as good as the policies of the weakest link in the chain.

この事実を説明するのを助けるために、次の例を考えてみましょう。悪質なドメイン - 独自のドメイン外のユーザーを示し、偽P-アサート-アイデンティティとのINVITE要求をSIPを送りたい、私たちはspam.example.comそれらを呼びましょう。 spam.example.comが原因スパムでその小さなサイズと無関心に、検証せずに顧客から任意のP-アサート・アイデンティティを受け入れ、小さな国の地域SIPプロバイダを見つけました。このプロバイダは、順番に、より大きな、相互接続プロバイダに接続します。彼らは、P-アサート・アイデンティティを確認するために、顧客のそれぞれを頼むんが、それを強制する簡単な方法がありません。このプロバイダは、順番に、他の皆に接続します。その結果、spam.example.comドメインは、偽装された発信者IDを持つ呼び出しを注入することができます。この要求は、ネットワークを介して到達可能な任意の受信者(ルート・プロバイダの大きなサイズに起因し、おそらく皆)に向けることができます。受信者は、この特定のP-アサート-アイデンティティは、この悪いspam.example.comドメインから来たことを知ってする方法はありません。例が示すように、中央のプロバイダの政策が良いにもかかわらず、P-アサート - アイデンティティの全体的な効果はまだチェーンの最も弱いリンクの政策と同じくらい良いです。

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.


6. Framework for Anti-Spam in SIP

Unfortunately, there is no magic bullet for preventing SIP spam, just as there is none for email spam. However, the combination of several techniques can provide a framework for dealing with spam in SIP. This section provides recommendations for network designers in order to help mitigate the risk of spam.


There are four core recommendations that can be made:


Strong Identity: Firstly, 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. Consent, reputation systems, computational puzzles, and payments at risk, amongst others, all work best when applied only to new requests, and successful completion of an introduction results in the placement of a user on a white list. However, usage of white lists depends on strong identity assertions. Consequently, any network that interconnects with others should make use of strong SIP identity as described in RFC 4474. P-Asserted-Identity is not strong enough.

強力なアイデンティティ:まず、ほぼすべての上述の解決策の中で、SIPメッセージのドメイン間の送信者を認証する能力に依存性があります。唯一の新しい要求、およびホワイトリスト上のユーザの配置で導入結果が正常に完了に適用されたときに同意、評判システム、計算パズル、およびリスクの支払いは、とりわけ、すべてが最高の仕事します。しかし、ホワイトリストの使用方法は、強力なアイデンティティのアサーションに依存します。 P-アサート-アイデンティティが十分に強くないRFC 4474.に記載されその結果、他の人と相互接続するネットワークは、強力なSIPアイデンティティの使用をしなければなりません。

White Lists: Secondly, with a strong identity system in place, networks are recommended to make use of white lists. These are ideally built off existing buddy lists, if present. If not, separate white lists can be managed for spam. Placement on these lists can be manual or based on the successful completion of one or more introduction mechanisms.


Solve the Introduction Problem: This in turn leads to the final recommendation to be made. Network designers should make use of one or more mechanisms meant to solve the introduction problem.


Indeed, it is possible to use more than one and combine the results through some kind of weight. A user that successfully completes the introduction mechanism can be automatically added to the white list. Of course, that can only be done usefully if their identity is verified by SIP Identity. The set of mechanisms for solving the introduction problem, as described in this document, are based on some (but not all) of the techniques known and used at the time of writing. 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.

確かに、それ以上のものを使用し、重量のいくつかの種類によって結果を組み合わせることが可能です。首尾よく導入機構を完了したユーザーは、自動的にホワイトリストに追加することができます。自分のアイデンティティをSIPアイデンティティによって検証された場合はもちろん、それだけで有効に行うことができます。導入の問題を解決するためのメカニズムの組は、この文書に記載されているように、書き込み時に知られており、使用される技術のいくつか(全てではない)に基づいています。 SIPサービスのプロバイダは、彼らが進化すると、電子メールでのソリューションのタブを維持し、それらの技術を提供しなければならないものの最高を活用すべきです。

Don't Wait Until It's Too Late: But perhaps most importantly, providers should not ignore the spam problem until it happens! 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.


7. Additional Work

Though the above framework serves as a good foundation on which to deal with spam in SIP, there are gaps, some of which can be addressed by additional work that has yet to be undertaken.


One of the difficulties with the strong identity techniques is that a receiver of a SIP request without an authenticated identity cannot know whether the request lacked such an identity because the originating domain didn't support it, or because a man-in-the-middle removed it. As a result, transition mechanisms should be put in place to allow these to be differentiated. Without it, the value of the identity mechanism is much reduced.


8. Security Considerations

This document is entirely devoted to issues relating to spam in SIP and references a variety of security mechanisms in support of that goal.


9. 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 and Vijay Gurbani for their reviews. Useful comments and feedback were provided by Nils Ohlmeir, Tony Finch, Randy Gellens, Lisa Dusseault, Sam Hartman, Chris Newman, Tim Polk, Donald Eastlake, and Yakov Shafranovich. Jon Peterson wrote some of the text in this document and has contributed to the work as it has moved along.


10. Informative References

[1] Campbell, B., Mahy, R., and C. Jennings, "The Message Session Relay Protocol (MSRP)", RFC 4975, September 2007.

[1]キャンベル、B.、マーイ、R.、およびC.ジェニングス、 "メッセージセッションリレープロトコル(MSRP)"、RFC 4975、2007年9月。

[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.

[2]ローゼンバーグ、J.、Schulzrinneと、H.、カマリロ、G.、ジョンストン、A.、ピーターソン、J.、スパークス、R.、ハンドレー、M.、およびE.学生、 "SIP:セッション開始プロトコル" 、RFC 3261、2002年6月。

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

[3]キャンベル、B.、ローゼンバーグ、J.、Schulzrinneと、H.、のHuitema、C.、およびD. Gurle、 "インスタントメッセージングのためのセッション開始プロトコル(SIP)拡張子"、RFC 3428、2002年12月。

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

[4]ローチ、A.、 "セッション開始プロトコル(SIP)特異的イベント通知"、RFC 3265、2002年6月。

[5] 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.

[5]ジェニングス、C.、ピーターソン、J.、およびM.ワトソン、 "信頼できるネットワーク内のアサート・アイデンティティのためのセッション開始プロトコル(SIP)のプライベート拡張"、RFC 3325、2002年11月。

[6] Rosenberg, J., "A Presence Event Package for the Session Initiation Protocol (SIP)", RFC 3856, August 2004.

[6]ローゼンバーグ、J.、 "セッション開始プロトコルのためのプレゼンスイベントパッケージ(SIP)"、RFC 3856、2004年8月。

[7] Rosenberg, J., "A Watcher Information Event Template-Package for the Session Initiation Protocol (SIP)", RFC 3857, August 2004.

[7]ローゼンバーグ、J.、RFC 3857、2004年8月 "セッション開始プロトコル(SIP)のためのウォッチャー情報イベントテンプレート・パッケージ"。

[8] Rosenberg, J., "An Extensible Markup Language (XML) Based Format for Watcher Information", RFC 3858, August 2004.

[8]ローゼンバーグ、J.、 "ウォッチャー情報のための拡張マークアップ言語(XML)ベースのフォーマット"、RFC 3858、2004年8月を。

[9] Faltstrom, P. and M. Mealling, "The E.164 to Uniform Resource Identifiers (URI) Dynamic Delegation Discovery System (DDDS) Application (ENUM)", RFC 3761, April 2004.

[9] Faltstrom、P.及びM. Mealling、 "ユニフォームリソース識別子にE.164(URI)ダイナミックな委譲発見システム(DDDS)アプリケーション(ENUM)"、RFC 3761、2004年4月。

[10] Rosenberg, J., "The Extensible Markup Language (XML) Configuration Access Protocol (XCAP)", RFC 4825, May 2007.

[10]ローゼンバーグ、J.、 "拡張マークアップ言語(XML)設定アクセスプロトコル(XCAP)"、RFC 4825、2007年5月。

[11] Rosenberg, J., "Presence Authorization Rules", RFC 5025, October 2007.

[11]ローゼンバーグ、J.、 "プレゼンス認証ルール"、RFC 5025、2007年10月。

[12] Rosenberg, J., "A Framework for Consent-Based Communications in the Session Initiation Protocol (SIP)", Work in Progress, October 2007.


[13] Camarillo, G., "A Document Format for Requesting Consent", Work in Progress, October 2007.


[14] Rosenberg, J., "A Framework for Application Interaction in the Session Initiation Protocol (SIP)", Work in Progress, October 2005.


[15] Burger, E. and M. Dolly, "A Session Initiation Protocol (SIP) Event Package for Key Press Stimulus (KPML)", RFC 4730, November 2006.

[15]バーガー、E.およびM.ドリー、 "Aセッション開始プロトコル(SIP)キーを押して刺激のためのイベントパッケージ(KPML)"、RFC 4730、2006年11月。

[16] Rosenberg, J., "Applying Loose Routing to Session Initiation Protocol (SIP) User Agents (UA)", Work in Progress, June 2007.

[16]ローゼンバーグ、J.、進歩、2007年6月に仕事 "セッション開始プロトコル(SIP)ユーザエージェント(UA)にルースルーティングの適用"。

[17] Peterson, J. and C. Jennings, "Enhancements for Authenticated Identity Management in the Session Initiation Protocol (SIP)", RFC 4474, August 2006.

[17]ピーターソン、J.とC.ジェニングス、 "セッション開始プロトコル(SIP)で認証されたアイデンティティ管理のための機能強化"、RFC 4474、2006年8月。

[18] Allman, E. and H. Katz, "SMTP Service Extension for Indicating the Responsible Submitter of an E-Mail Message", RFC 4405, April 2006.

[18]オールマン、E.およびH.カッツ、「電子メールメッセージの責任提出者を示すためのSMTPサービス拡張」、RFC 4405、2006年4月。

[19] Lyon, J. and M. Wong, "Sender ID: Authenticating E-Mail", RFC 4406, April 2006.

[19]リヨン、J.とM.ウォン、 "送信者ID:認証の電子メール"、RFC 4406、2006年4月。

[20] Lyon, J., "Purported Responsible Address in E-Mail Messages", RFC 4407, April 2006.

[20]リヨン、J.、 "Eメールメッセージで主張責任アドレス"、RFC 4407、2006年4月。

[21] Wong, M. and W. Schlitt, "Sender Policy Framework (SPF) for Authorizing Use of Domains in E-Mail, Version 1", RFC 4408, April 2006.

"Eメール、バージョン1でのドメインの認可使用のためのSPF(Sender Policy Framework)を" [21]ウォン、M.およびW. Schlitt、RFC 4408、2006年4月。

[22] Dierks, T. and E. Rescorla, "The Transport Layer Security (TLS) Protocol Version 1.1", RFC 4346, April 2006.

[22]ダークス、T.およびE.レスコラ、 "トランスポート層セキュリティ(TLS)プロトコルバージョン1.1"、RFC 4346、2006年4月。

[23] Allman, E., Callas, J., Delany, M., Libbey, M., Fenton, J., and M. Thomas, "DomainKeys Identified Mail (DKIM) Signatures", RFC 4871, May 2007.

[23]オールマン、E.、カラス、J.、デラニー、M.、リビー、M.、フェントン、J.、およびM.トーマス、 "ドメインキーを識別メール(DKIM)署名"、RFC 4871、2007年5月。

[24] Ramsdell, B., "Secure/Multipurpose Internet Mail Extensions (S/MIME) Version 3.1 Message Specification", RFC 3851, July 2004.

[24] Ramsdell、B.、 "/セキュア多目的インターネットメール拡張(S / MIME)バージョン3.1メッセージ仕様"、RFC 3851、2004年7月。

[25] Elkins, M., Del Torto, D., Levien, R., and T. Roessler, "MIME Security with OpenPGP", RFC 3156, August 2001.

[25]エルキンズ、M.、デルTorto、D.、Levien、R.、およびT.レスラー、 "OpenPGPのとMIMEセキュリティ"、RFC 3156、2001年8月。

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

[26]アバディ、M.、バローズ、M.、Manasse、M.、およびT. Wobber、 "適度にハード、メモリーバウンド機能、NDSS 2003"、2003年2月。

[27] 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 2003.

[27]アバディ、M.、バローズ、M.、ビレル、A.、Dabek、F.、およびT. Wobber、 "ネットワークサービスのための確かな切手、8日のアジアコンピューティング科学会議、ムンバイ、インドの議事録"、12月2003。

[28] Clayton, R. and B. Laurie, "Proof of Work Proves not to Work, Third Annual Workshop on Economics and Information Security", May 2004.


Authors' Addresses


Jonathan Rosenberg Cisco Edison, NJ US

ジョナサン・ローゼンバーグシスコエジソン、NJ US

EMail: URI:

電子メール URI:

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

カレン・ジェニングスのCisco 170西タスマン博士サンノゼ、CA 95134米国

Phone: +1 408 421-9990 EMail:

電話:+1 408 421-9990 Eメール

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