HTTP/1.1 200 OK Date: Tue, 09 Apr 2002 01:40:25 GMT Server: Apache/1.3.20 (Unix) Last-Modified: Thu, 07 May 1998 01:32:00 GMT ETag: "2ed69e-a739-35510f10" Accept-Ranges: bytes Content-Length: 42809 Connection: close Content-Type: text/plain IETF media feature registration WG Graham Klyne Internet draft Content Technologies Ltd. 5 May 1998 Expires: 5 November 1998 An algebra for describing media feature sets Status of this memo This document is an Internet-Draft. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as Internet-Drafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as ``work in progress''. To view the entire list of current Internet-Drafts, please check the "1id-abstracts.txt" listing contained in the Internet-Drafts Shadow Directories on ftp.is.co.za (Africa), ftp.nordu.net (Northern Europe), ftp.nis.garr.it (Southern Europe), munnari.oz.au (Pacific Rim), ftp.ietf.org (US East Coast), or ftp.isi.edu (US West Coast). Copyright (C) 1998, The Internet Society Abstract A number of Internet application protocols have a need to provide content negotiation for the resources with which they interact [1]. A framework for such negotiation is described in [2]. Part of this framework is a way to describe the range of media features which can be handled by the sender, recipient or document transmission format of a message. A format for a vocabulary of individual media features and procedures for registering media features are presented in [3]. This document describes an algebra which can be used to define feature sets which are formed from combinations and relations involving individual media features. Such feature sets are used to describe the media feature handling capabilities of message senders, recipients and file formats. Klyne [Page 1] Internet draft 5 May 1998 An algebra for describing media feature sets Table of contents 1. Introduction.............................................2 1.1 Structure of this document ...........................3 1.2 Discussion of this document ..........................4 1.3 Ammendment history ...................................4 1.4 Unfinished business ..................................4 2. Terminology and definitions..............................4 3. Media feature values.....................................5 3.1 Complexity of feature algebra ........................5 3.2 Sufficiency of simple types ..........................6 3.2.1 Unstructured data types..........................6 3.2.2 Cartesian product................................6 3.2.3 Disciminated union...............................7 3.2.4 Array............................................7 3.2.5 Powerset.........................................8 3.2.6 Sequence.........................................8 4. Feature set predicates...................................8 4.1 An algebra for data file format selection ............9 4.1.1 Describing file format features..................10 4.1.1.1 Feature ranges 10 4.1.1.2 Feature combinations 11 (A) Additional predicates 11 (B) Meta-features as groupings of other features 12 4.1.2 Content, sender and recipient capabilities.......12 4.2 Conclusion and proposal ..............................12 5. Indicating preferences...................................13 5.1 Combining preferences ................................13 5.2 Representing preferences .............................14 6. Feature set representation...............................15 6.1 Text string representation ...........................16 6.2 ASN.1 representation .................................17 7. Security considerations..................................18 8. Copyright................................................19 9. Acknowledgements.........................................19 10. References..............................................19 11. Author's address........................................21 1. Introduction A number of Internet application protocols have a need to provide content negotiation for the resources with which they interact [1]. A framework for such negotiation is described in [2]. A part of this framework is a way to describe the range of media features which can be handled by the sender, recipient or document transmission format of a message. Klyne [Page 2] Internet draft 5 May 1998 An algebra for describing media feature sets Descriptions of media feature capabilities need to be based upon some underlying vocabulary of individual media features. A format for such a vocabulary and procedures for registering media features are presented in [3]. This document defines an algebra which can be used to describe feature sets which are formed from combinations and relations involving individual media features. Such feature sets are used to describe the media handling capabilities of message senders, recipients and file formats. The feature set algebra is built around the principle of using feature set predicates as mathematical relations which define constraints on feature handling capabilities. The idea is that the same form of feature set expression can be used to describe sender, receiver and file format capabilities. This has been loosely modelled on the way that the Prolog programming language uses Horn Clauses to describe a set of result values. In developing the algebra, axamples are given using notation drawn from the C and Prolog programming languages. A syntax for expressing feature predicates is suggested, based on LDAP search filters. 1.1 Structure of this document The main part of this draft addresses the following main areas: Section 2 introduces and references some terms which are used with special meaning. Section 3 discusses constraints on the data types allowed for individual media feature values. Section 4 introduces and describes the algebra used to construct feature set descriptions with expressions containing media features. The first part of this section contains a development of the ideas, and the second part contains the conclusions and proposed algebra. Section 5 introduces and describes extensions to the algebra for indicating preferences between different feature sets. Section 6 contains a description of recommended representations for describing feature sets based on the previously-described algebra. Klyne [Page 3] Internet draft 5 May 1998 An algebra for describing media feature sets 1.2 Discussion of this document Discussion of this document should take place on the content negotiation and media feature reagistration mailing list hosted by the Internet Mail Consortium (IMC): Please send comments regarding this document to: ietf-medfree@imc.org To subscribe to this list, send a message with the body 'subscribe' to "ietf-medfree-request@imc.org". To see what has gone on before you subscribed, please see the mailing list archive at: http://www.imc.org/ietf-medfree/ 1.3 Ammendment history 00a 11-Mar-1998 Document initially created. 01a 05-May-1998 Mainly-editorial revision of sections describing the feature types and algebra. Added section on indicating preferences. Added section describing feature predicate syntax. Added to security considerations (based on fax negotiation scenarios draft). 1.4 Unfinished business . Array values: are they needed? (section 3.2.4) . Use of unknown data types for feature values (section 6) . Is a test for presence of a feature required? (section 6) . Should ASN.1 representation be pursued? If so, should it be aligned with LDAP filter representation? (section 6.2) 2. Terminology and definitions Feature Collection is a collection of different media features and associated values. This might be viewed as describing a specific rendering of a specific instance of a document or resource by a specific recipient. Klyne [Page 4] Internet draft 5 May 1998 An algebra for describing media feature sets Feature Set is a set of zero, one or more feature collections. Feature set predicate A function of an arbitrary feature collection value which returns a Boolean result. A TRUE result is taken to mean that the corresponding feature collection belongs to some set of media feature handling capabilities defined by the predicate. Other terms used in this draft are defined in [2]. 3. Media feature values This document assumes that individual media feature values are simple atomic values: . Boolean values . Enumerated values . Numeric values More complex media feature values might be accommodated, but they would (a) be undesirable because they would complicate the algebra, and (b) are not necessary. These statements are justified in the following sub-sections. 3.1 Complexity of feature algebra Statement (a) above is justified as follows: predicates constructed as expressions containing media feature values must ultimately resolve to a logical combination of feature value tests. A full range of simple tests for all of the data types listed above can be performed based on just two fundamental operations: equality and less-than. All other meaningful tests can be constructed as predicates incorporating these two basic tests. For example: ( a != b ) iff !( a == b ) ( a <= b ) iff !( b < a ) ( a > b ) iff ( b < a ) ( a >= b ) iff !( a < b ) Klyne [Page 5] Internet draft 5 May 1998 An algebra for describing media feature sets If additional (composite) data types are introduced, then additional operators must be introduced to test their component parts: the addition of just one further comparison operator increases the number of such operators by 50%. 3.2 Sufficiency of simple types To justify statement (b), let us first review the range of composite data types that might reasonably be considered. In 1972, a paper "Notes on data structuring" by C. A. R. Hoare was published in the book "Structured Programming" [4]. This was an early formalization of data types used in programming languages, and its content has formed a sufficient basis for describing the data types in almost every programming language which has been developed. This gives good grounds to believe that the type framework is also sufficient for media features. The data types covered by Hoare's paper are: . Unstructured data types: (integer, real, enumeration, ordered enumeration, subranges). . Cartesian product (e.g. C 'struct'). . Discriminated union (e.g. C 'union'). . Array. . Powerset (e.g. Pascal 'SET OF'). . Sequence (e.g. C string, Pascal 'FILE OF'). To demonstrate sufficiency of simple types for media features we must show that the feature-set defining properties of these composite types can be captured using predicates on the simple simple types described previously. 3.2.1 Unstructured data types The unstructured data types noted correspond closely to, and can be represented by the proposed simple value types for media features. 3.2.2 Cartesian product A cartesian product value (e.g. resolution=[x,y]) is easily captured as a collection of two or more separately named media features (e.g. x-resolution=x, y-resolution=y). Klyne [Page 6] Internet draft 5 May 1998 An algebra for describing media feature sets 3.2.3 Disciminated union A discriminated union value is an either/or type of choice. For example, a given workstation might be able to display 16K colours at 1024x768 resolution, OR 256 colours at 1280x1024 resolution. These possibilities are captured by a logical-OR of predicates: ( ( x-resolution <= 1024 ) && ( y-resolution <= 768 ) && ( colours <= 16384 ) ) || ( ( x-resolution <= 1280 ) && ( y-resolution <= 1024 ) && ( colours <= 256 ) ) 3.2.4 Array An array represents a mapping from one data type to another. For example, the availability of pens in a pen plotter might be represented by an array which maps a pen number to a colour. If the array index which forms the basis for defining a feature set is assumed to be a constant, then each member can be designated by a feature name which incorporates the index value. For example: Pen-1=black, pen-2=red, etc. Another example where an array might describe a media feature is a colour palette: an array is used to associate a colour value (in terms of RGB or some other colour model) with a colour index value. In this case is is possible to envisage a requirement for a particular colour to be loaded in the palette without any knowledge of the index which maps to it. In this case, the colour might be treated as a named Boolean attribute: if TRUE then that colour is deemed to be available in the pallette Feature selection based on a variable array index is more difficult, but it is believed that this is not required for media selection. [[I cannot think of any example of feature selection which involves a variable index into an array. If such a feature is presented, an array type could be added to the set of allowable media feature types, and an array selection operator added to the algebra.]] Klyne [Page 7] Internet draft 5 May 1998 An algebra for describing media feature sets 3.2.5 Powerset A powerset is a collection of zero, one or more values from some base set of values. A colour palette may be viewed as a powerset of colour values, or the fonts available in a printer as a powerset of all available fonts. A powerset is very easily represented by a separate Boolean-valued feature for each member of the base set. The value TRUE indicates that the corresonding value is a member of the powerset value. 3.2.6 Sequence A sequence is a list of values from some base set of values, which are accessed sequentially. A sequence can be modelled by an array if one assumes integer index values starting at (say) 1 and incrementing by 1 for each successive element of the sequence. Thus, the considerations described above relating to array values can be considered as also applying (in part) to sequence values. That is, if arrays are deemed to be adequately handled, then sequence values too can be handled. 4. Feature set predicates A model for data file selection is proposed, based on relational set definition and subset selection, using elements of the Prolog programming language [5] as a descriptive notation for this purpose. NOTE: The use of Prolog as a syntax for feature description is NOT being proposed; rather, the Prolog- like notation is used to develop the semantics of an algebra. Once the semantics have been developed, they can be mapped to some convenient syntax. For the purposes of developing this algebra, examples are drawn from the media features described in "Media Features for Display, Print, and Fax" [6], which in summary are: pix-x=n (Image size, in pixels) pix-y=m res-x=n (Image resolution, pixels per inch) res-y=m Klyne [Page 8] Internet draft 5 May 1998 An algebra for describing media feature sets UA-media= screen|stationary|transparency|envelope| continuous-long papersize= na-letter|iso-A4|iso-B4|iso-A3|na-legal color=n (Colour depth in bits) grey=n (Grey scale depth in bits) 4.1 An algebra for data file format selection The basic idea proposed here is that a feature capability of the original content, sender, data file format or recipient is represented as a predicate applied to a collection of feature values. Under universal quantification (i.e. selecting all possible values that satisfy it), a predicate indicates a range of possible combinations of feature values). This idea is inherent in Prolog clause notation, which is used in the example below to describe a predicate 'acceptable_file_format(File)' which yields a set of possible file transfer formats using other predicates which indicate the file formats available to the sender and feature capabilities of the file format, original content: acceptable_file_format(File) :- sender_available_file_format(File), match_format(File). match_format(File) :- pix_x(File,Px), content_pix_x(Px), recipient_pix_x(Px), pix_y(File,Py), content_pix_x(Py), recipient_pix_y(Py), res_x(File,Rx), content_res_x(Rx), recipient_res_x(Rx), res_y(File,Ry), content_res_y(Ry), recipient_res_y(Ry), colour(File,C), content_colour(C), recipient_colour(C), grey(File,G), content_grey(G), recipient_grey(G), ua_media(File,M), content_ua_media(M), recipient_ua_media(M), papersize(File,P), content_papersize(P), recipient_papersize(P). Essentially, this selects a set of file transfer formats from those available ('sender_available_file_format'), choosing any whose feature capabilities have a non-empty intersection with the feature capabilities of the original content and the recipient. Klyne [Page 9] Internet draft 5 May 1998 An algebra for describing media feature sets 4.1.1 Describing file format features The above framework suggests a file format is described by a set of feature values. As an abstract theory, this works fine but for practical use it has a couple of problems: (a) description of features with a large number of possibilities (b) describing features which are supported in specific combinations A typical case of (a) would be where a feature (e.g. size of image in pixels) can take any value from a range. To present and test each value separately is not a practical proposition, even if it were possible. (A guide here as to what constitutes a practical approach is to make a judgement about the feasibility of writing the corresponding Prolog program.) A typical case of (b) would be where different values for certain features can occur only in combinations (e.g. allowable combinations of resolution and colour depth on a given video display). If the features are treated independently as suggested by the framework above, all possible combinations would be allowed, rather than the specifically allowable combinations. 4.1.1.1 Feature ranges The first issue can be addressed by considering the type of value which can represent the allowed features of a data file format. The features of a specific data file are represented as values from an enumeration (e.g. ua_media, papersize), or a numeric values (integer or rational). The description of allowable file format feature needs to represent all the allowable values. The Prolog clauses used above to describe file format features already allow for multiple enumerated values. Each acts as a mathematical relation to select a subset of the set of file values allowed by the preceding predicates. Section 3 of this document describes proposed media feature value types. For numeric feature values, a sequence of two numbers to represent a closed interval is suggested, where either value may be replaced by an empty list to indicate no limiting value. Thus: [m,n] => { x : m <= x <= n } [m,[]] => { x : m <= x } [[],n] => { x : x <= n } Klyne [Page 10] Internet draft 5 May 1998 An algebra for describing media feature sets The following Prolog could be used to describe such range matching: feature_match(X,[[],[]]). feature_match(X,[L,[]]) :- L <= X. feature_match(X,[[],H]) :- X <= H. feature_match(X,[L,H]) :- L <= X, X <= H. feature_match(X,X). (This example strectches standard Prolog, which does not support non-integer numbers. The final clause allows 'feature_match' to deal with equality matching for the normal enumerated value case.) 4.1.1.2 Feature combinations Representing allowed combinations of features is trickier. Two possible approaches might be considered: (a) use additional predicates to impose relationships between features. (b) allow meta-features which are groupings of other features. (A) Additional predicates If x- and y- resolutions were to be constrained to square or semi- square aspect-ratios, the following predicates might be added to the feature set description: ( feature_match(Rx,Ry) ; feature_match(Rx,2*Ry) ; feature_match(2*Rx,Ry) ), feature_match(Rx,[72,600]), feature_match(Ry,[72,600]) (where the last two constraints might be imposed by the 'res_x' and 'res_y' predicates). Another example might be: ( ( feature_match(Px,640), feature_match(Py,480) ) ; ( feature_match(Px,600), feature_match(Py,800) ) ; ( feature_match(Px,1024), feature_match(Py,768) ) ) This is based on the predicates 'pix_x(File,Px)', 'pix_y(File,Py)', 'res_x(File,Rx)' and 'res_y(File,Ry)' from the initial framework above.) Klyne [Page 11] Internet draft 5 May 1998 An algebra for describing media feature sets (B) Meta-features as groupings of other features Applying this to the above examples would replace: pix_x(File,Px), pix_y(File,Py), res_x(File,Rx), res_y(File,Ry), with the meta-features 'pix' and 'res': pix(File,[Px,Py]), res(File,[Rx,Ry]) where: pix(File,[640, 480]). pix(File,[800, 600]). pix(File,[1024,768]). res(File,[Rx,Ry]) :- feature_match(Rx,[72,600]), feature_match(Ry,[72,600]), ( feature_match(Rx,Ry) ; feature_match(Rx,2*Ry) ; feature_match(2*Rx,Ry) ). On closer examination, these two options turn out to be pretty much the same thing: a requirement to impose additional constraint predicates on a file feature set. They differ only in where the predicates are applied. This all suggests that file format capabilities can be described by feature set predicates: arbitrary logical expressions using AND, OR, NOT logical combining operators, and media feature value matching. 4.1.2 Content, sender and recipient capabilities It has already been suggested that these are represented as predicates on the feature set of a particular data file. Having also shown that these same predicates can represent constraints on feature combinations, we proceed directly to a proposal that everything is represented by predicates. 4.2 Conclusion and proposal Data file features, original content features, sender features and recipient features (and user features) can all be represented as predicates. Klyne [Page 12] Internet draft 5 May 1998 An algebra for describing media feature sets A key insight, which points to this conclusion, is that a collection of feature values can be viewed as describing a specific document rendered by a specific recipient. The capabilities that we wish to describe, be they sender, file format, recipient or other capabilities, are sets of such feature collections, with the potential to ultimately render using any of the feature value collections in the set. This raises a terminology problem, because the term "feature set" has been used to mean a collection of specific feature values and a range of possible feature values. Thus the more restricted definitions of "feature collection" and "feature set" which appear in the terminology section of this document. Original content, data files and recipients (and users) all embody the potential capability to deal with a "feature set". One of the aims of content negotiation is to select an available data file format (availability being circumscribed by the original content and sender capabilities) whose feature set intersection with the recipient feature set is non-empty. (The further issue of preference being deferred for later consideration.) The concept of a mathematical relation as a subset defined by a predicate can be used to define feature sets, using universal quantification (i.e. using the predicate to select from some notional universe of all possible feature collections). Thus, a common framework of predicates can be used to represent the feature capabilities of original content, data file formats, recipients and any other participating entity which may impose constraints on the usable feature sets. Within this framework, it is sufficient to represent individual feature values as enumerated values or numeric ranges. The thesis in section 3 of his document, combined with a study of "Media Features for Display, Print, and Fax" [6], indicate that more complex media feature values can be handled by predicates. 5. Indicating preferences 5.1 Combining preferences The general problem of describing and combining preferences among feature sets is very much more complex than simply describing allowable feature sets. For example, given two feature sets: {A1,B1} {A2,B2} Klyne [Page 13] Internet draft 5 May 1998 An algebra for describing media feature sets where: A1 is preferred over A2 B2 is preferred over B1 which of the feature sets is preferred? In the absence of additional information or assumptions, there is no generally satisfactory answer to this. The proposed resolution of this issue is simply to assert that preference information cannot be combined. Applied to the above example, any preference information about A1 in relation to A2, or B1 in relation to B2 is not presumed to convey any information about preference of {A1,B1} in relation to {A2,B2}. (This approach was selected as being the simplest among those considered, and because there is no clear need for anything more). In practical terms, this restricts the aplication of preference information to top-level predicate clauses. A top-level clause completely defines an allowable feature set; clauses combined by logical-AND operators cannot be top-level clauses. 5.2 Representing preferences A convenient way to represent preferences is by numeric "quality values", as used in HTTP "Accept" headers, etc. (see RFC 2068 [9], section 3.9]). It has been suggested that numeric quality values, as used in some HTTP negotiations, are misleading and are really just a way of ranking options. Attempts to perform arithmetic on quality values do seem to degenerate into meaningless juggling of numbers. Numeric quality values in the range 0 to 1 (as defined by RFC 2068 [9], section 3.9) are used to rank feature sets according to preference. Higher values are preferred over lower values, and equal values are presumed to be equally preferred. Beyond this, the actual number used has no significance, and should not be used as a basis for any arithmetic operation. In the absence of any explcitly applied quality value, a value of "1" is assumed, suggesting an option which is equally or more preferred than any other. This approach can be represented in the Prolog-based framework of an earlier example as follows: match_format(File,Qvalue) :- match_format(File), Qvalue=1. Klyne [Page 14] Internet draft 5 May 1998 An algebra for describing media feature sets match_format(File) :- pix(File,[1024,768], res(File,[Rx,Ry]). match_format(File,Q) :- pix(File,[800, 600]), res(File,[Rx,Ry]), Qvalue=0.9. match_format(File,Q) :- pix(File,[640, 480]). res(File,[Rx,Ry]), Qvalue=0.8. res(File,[Rx,Ry]) :- feature_match(Rx,[72,600]), feature_match(Ry,[72,600]), ( feature_match(Rx,Ry) ; feature_match(Rx,2*Ry) ; feature_match(2*Rx,Ry) ). This example applies image preference ranking based solely on the size of the image, provided that the resolution constrains are satisfied. 6. Feature set representation The foregoing sections have desribed a framework and semantics for defining feature sets with predicates applied to feature collections. This section proposes some concrete representations for these feature setpredicates. Rather than invent an all-new notation, this proposal adapts a notation already defined for directory access [7,8]. Observe that a feature collection is similar to a directory entry, in that it consists of a collection of named values. Further, the semantics of the mechanism for selecting feature collections from a feature set is in most respects identical to selection of directory entries from a directory. Differences between directory selection (per [7]) and feature set selection described previously are: . Directory selection provides substring-, approximate- and extensible- matching for attribute values. Directory selection may also be based on the presence of an attribute without regard to its value. Klyne [Page 15] Internet draft 5 May 1998 An algebra for describing media feature sets . Directory selection provides for matching rules which are dependent upon the declared data type of an attribute value. . Feature selection provides for the association of a quality value with a top-level feature predicate as a way of ranking the selected value collections. The idea of substring matching does not seem to be relevant to feature set selection, and is excluded from these proposals. The idea of extensible matching and matching rules dependent upon data types are facets of a problem not addressed by this memo, but which do not necessarily affect the feature selection syntax. An aspect which might have a bearing on the syntax would be a requirement to specify a matching rule explicitly as part of a selection expression. Testing for the presence of a feature may be useful in some circumstances, but does not sit comfortably within the semantic framework. Feature sets are described by universal quantification over predicates, and the absence of reference to a given feature means the set is not constrained by that feature. Against this, it is difficult to define what might be meant by "presence" of a feature, so this option is not included in these proposals. 6.1 Text string representation The text representation of a feature set is closely based on RFC 2254 "The String Representation of LDAP Search Filters" [8], excluding those elements not relevant to feature set selection (discussed above), and adding options to associate quality values with top-level predicates. The format of a feature predicate is defined by the production for "filter" in the following, using the syntax notation of [10]: filter = "(" filtercomp [ ";" "q=" qvalue ] )" qvalue = ( "0" [ "." 0*3DIGIT ] ) / ( "1" [ "." 0*3("0") ] ) filtercomp = and / or / not / item and = "&" filterlist or = "|" filterlist not = "!" filter filterlist = 1*filter item = simple Klyne [Page 16] Internet draft 5 May 1998 An algebra for describing media feature sets simple = attr filtertype value filtertype = equal / greater / less equal = "=" approx = "~=" greater = ">=" less = "<=" attr = value = As described, the syntax permits a quality value to be attached to any "filter" value in the predicate (not just top-level values). But it should be noted that values which are enclosed by "not" or "and" constructs are not visible to the enclosing context. If a given feature collection is matched by more than one "filter" in an "or" clause, the highest associated quality value is applied. NOTE The flexible approach to allowable quality values in this syntax has been adopted for two reasons: (a) to make it easy to combine separately constructed feature predicates, and (b) to allow that the mechanism used for quality values might, in future, be generalized to an extensible tagging mechanism (for example, to incorporate a conceivable requirement to explicitly specify a matching rule). 6.2 ASN.1 representation Should it be required, the LDAP search filter model provides the basis for an ASN.1 representation of a feature predicate. The following ASN.1 is adapted from RFC 2251 "Lightweight Directory Access Protocol (v3)" [7] (also contained in RFC 2254 "The String Representation of LDAP Search Filters" [8]) to mirror the adaptation of the string representation presented above [[The following ASN.1 fragment does not include provision for quality value (and possibly other parameter values) to be attached to a filter value. Also, if using an ASN.1-derived representation it would seem more appropriate to use an ISO object identifier for the feature tag, and an appropriate ASN.1 type for the feature value. Such changes would remove any semblance of compatibility with LDAP, but that may not matter.]] Klyne [Page 17] Internet draft 5 May 1998 An algebra for describing media feature sets Filter ::= CHOICE { and [0] SET OF Filter, or [1] SET OF Filter, not [2] Filter, equalityMatch [3] AttributeValueAssertion, greaterOrEqual [5] AttributeValueAssertion, lessOrEqual [6] AttributeValueAssertion } AttributeValueAssertion ::= SEQUENCE { featureTag OCTET STRING, featureValue OCTET STRING } 7. Security considerations Some security considerations for content negotiation are raised in [1,2,3]. The following are primary security concerns for capability identification mechanisms: . Unintentional disclosure of private information through the announcement of capabilities or user preferences. . Disruption to system operation caused by accidental or malicious provision of incorrect capability information. . Use of a capability identification mechanism might be used to probe a network (e.g. by identifying specific hosts used, and exploiting their known weaknesses). The most contentious security concerns are raised by mechanisms which automatically send capability identification data in response to a query from some unknown system. Use of directory services (based on LDAP [7], etc.) seem to be less problematic because proper authentication mechanisms are available. Mechanisms which provide capability information when sending a message are less contentious, presumably because some intention can be inferred that person whose details are disclosed wishes to communicate with the recipient of those details. This does not, however, solve problems of spoofed supply of incorrect capability information. The use of format converting gateways may prove problematic because such systems would tend to defeat any message integrity and authenticity checking mechanisms that are employed. Klyne [Page 18] Internet draft 5 May 1998 An algebra for describing media feature sets 8. Copyright Copyright (C) The Internet Society 1998. All Rights Reserved. This document and translations of it may be copied and furnished to others, and derivative works that comment on or otherwise explain it or assist in its implementation may be prepared, copied, published and distributed, in whole or in part, without restriction of any kind, provided that the above copyright notice and this paragraph are included on all such copies and derivative works. However, this document itself may not be modified in any way, such as by removing the copyright notice or references to the Internet Society or other Internet organizations, except as needed for the purpose of developing Internet standards in which case the procedures for copyrights defined in the Internet Standards process must be followed, or as required to translate it into languages other than English. The limited permissions granted above are perpetual and will not be revoked by the Internet Society or its successors or assigns. This document and the information contained herein is provided on an "AS IS" basis and THE INTERNET SOCIETY AND THE INTERNET ENGINEERING TASK FORCE DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. 9. Acknowledgements My thanks to Larry Masinter for demonstrating to me the breadth of the media feature issue, and encouraging me to air my early ideas. Early discussions of ideas on the IETF-HTTP and IETF-FAX discussion lists led to useful inputs also from Koen Holtman, Ted Hardie and Dan Wing. The debate later moved to the IETF conneg WG mailing list, where Al Gilman was particularly helpful in helping me to refine the feature set algebra. Several ideas for indicating preferences were suggested by Larry Masinter. 10. References [1] "Scenarios for the Delivery of Negotiated Content" T. Hardie, NASA Network Information Center Internet draft: Work in progress, November 1997. Klyne [Page 19] Internet draft 5 May 1998 An algebra for describing media feature sets [2] "Requirements for protocol-independent content negotiation" G. Klyne, Integralis Ltd. Internet draft: Work in progress, March 1998. [3] "Content feature tag registration procedures" Koen Holtman, TUE Andrew Mutz, Hewlett-Packard Ted Hardie, NASA Internet draft: Work in progress, November 1997. [4] "Notes on data structuring" C. A. R. Hoare, in "Structured Programming" Academic Press, APIC Studies in Data Processing No. 8 ISBN 0-12-200550-3 / 0-12-200556-2 1972. [5] "Programming in Prolog" (2nd edition) W. F. Clocksin and C. S. Mellish, Springer Verlag ISBN 3-540-15011-0 / 0-387-15011-0 1984. [6] "Media Features for Display, Print, and Fax" Larry Masinter, Xerox PARC Koen Holtman, TUE Andrew Mutz, Hewlett-Packard Dan Wing, Cisco Systems Internet draft: Work in progress, January 1998. [7] RFC 2251, "Lightweight Directory Access Protocol (v3)" M. Wahl, Critical Angle Inc. T. Howes, Netscape Communications Corp. S. Kille, Isode Limited December 1997. [8] RFC 2254, "The String Representation of LDAP Search Filters" T. Howes, Netscape Communications Corp. December 1997. [9] RFC 2068, "Hyptertext Transfer Protocol -- HTTP/1.1" R. Fielding, UC Irvine J. Gettys, J. Mogul, DEC H. Frytyk, T. Berners-Lee, MIT/LCS January 1997. Klyne [Page 20] Internet draft 5 May 1998 An algebra for describing media feature sets [10] RFC 2234, "Augmented BNF for Syntax Specifications: ABNF" D. Crocker (editor), Internet Mail Consortium P. Overell, Demon Internet Ltd. November 1997. 11. Author's address Graham Klyne Content Technologies Ltd Forum 1 Station Road Theale Reading, RG7 4RA United Kingdom Telephone: +44 118 930 1300 Facsimile: +44 118 930 1301 E-mail: GK@ACM.ORG Klyne [Page 21]