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Network Working Group                                    P. Hallam-Baker
Internet-Draft                                         Comodo Group Inc.
Intended status: Standards Track                           March 7, 2016
Expires: September 8, 2016


                     Uniform Data Fingerprint (UDF)
                        draft-hallambaker-udf-03

Abstract

   This document describes means of generating Uniform Data Fingerprint
   (UDF) values and their presentation as text sequences and as URIs.

   Cryptographic digests provide a means of uniquely identifying static
   data without the need for a registration authority.  A fingerprint is
   a form of presenting a cryptographic digest that makes it suitable
   for use in applications where human readability is required.  The UDF
   fingerprint format improves over existing formats through the
   introduction of a compact algorithm identifier affording an
   intentionally limited choice of digest algorithm and the inclusion of
   an IANA registered Content-Type identifier within the scope of the
   digest input to allow the use of a single fingerprint format in
   multiple application domains.

   Alternative means of rendering fingerprint values are considered
   including machine readable codes, word and image lists.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   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."

   This Internet-Draft will expire on September 8, 2016.







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Copyright Notice

   Copyright (c) 2016 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents
   (http://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

1.  Definitions

1.1.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

2.  Introduction

   The use of cryptographic digest values as identifiers is well
   established as a means of generating a unique identifier for fixed
   data without the need for a registration authority.

   While the use of fingerprints of public keys was popularized by PGP,
   they are employed in many other applications including OpenPGP, SSH,
   BitCoin and PKIX.

   A cryptographic digest is a particular form of hash function that has
   the properties:

   It is easy to compute the digest value for any given message

   It is infeasible to generate a message from its digest value

   It is infeasible to modify a message without changing the digest
   value

   It is infeasible to find two different messages with the same digest
   value.

   If these properties are met, the only way that two data objects that
   map to the same digest value is by random chance.  If the number of



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   possible digest values is sufficiently large (i.e. is a sufficiently
   large number of bits in length), this chance is reduced to an
   arbitrarily infinitesimal probability.  Such values are described as
   being probabilistically unique.

   A fingerprint is a representation of a cryptographic digest value
   optimized for purposes of verification and in some cases data entry.

2.1.  Algorithm Identifier

   Although a secure cryptographic digest algorithm has properties that
   make it ideal for certain types of identifier use, several
   cryptographic digest algorithms have found widespread use, some of
   which have been demonstrated to be insecure.

   For example the MD5 message digest algorithm [RFC1321], was widely
   used in IETF protocols until it was demonstrated to be vulnerable to
   collision attacks [TBS].

   The secure use of a fingerprint scheme therefore requires the digest
   algorithm to either be fixed or otherwise determined by the
   fingerprint value itself.  Otherwise an attacker may be able to use a
   weak, broken digest algorithm to generate a data object matching a
   fingerprint value generated using a strong digest algorithm.

2.2.  Content Type Identifier

   A secure cryptographic digest algorithm provides a unique digest
   value that is probabilistically unique for a particular byte sequence
   but does not fix the context in which a byte sequence is interpreted.
   While such ambiguity may be tolerated in a fingerprint format
   designed for a single specific field of use, it is not acceptable in
   a general purpose format.

   For example, the SSH and OpenPGP applications both make use of
   fingerprints as identifiers for the public keys used but using
   different digest algorithms and data formats for representing the
   public key data.  While no such vulnerability has been demonstrated
   to date, it is certainly conceivable that a crafty attacker might
   construct an SSH key in such a fashion that OpenPGP interprets the
   data in an insecure fashion.  If the number of applications making
   use of fingerprint format that permits such substitutions is
   sufficiently large, the probability of a semantic substitution
   vulnerability being possible becomes unacceptably large.

   A simple control that defeats such attacks is to incorporate a
   content type identifier within the scope of the data input to the
   hash function.



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2.3.  Representation

   The representation of a fingerprint is the format in which it is
   presented to either an application or the user.

   Base32 encoding is used to produce the preferred text representation
   of a UDF fingerprint.  This encoding uses only the letters of the
   Latin alphabet with numbers chosen to minimize the risk of ambiguity
   between numbers and letters (2, 3, 4, 5, 6 and 7).

   To enhance readability and improve data entry, characters are grouped
   into groups of five.

2.4.  Truncation

   Different applications of fingerprints demand different tradeoffs
   between compactness of the representation and the number of
   significant bits.  A larger the number of significant bits reduces
   the risk of collision but at a cost to convenience.

   Modern cryptographic digest functions such as SHA-2 produce output
   values of at least 256 bits in length.  This is considerably larger
   than most uses of fingerprints require and certainly greater than can
   be represented in human readable form on a business card.

   Since a strong cryptographic digest function produces an output value
   in which every bit in the input value affects every bit in the output
   value with equal probability, it follows that truncating the digest
   value to produce a finger print is at least as strong as any other
   mechanism if digest algorithm used is strong.

   Using truncation to reduce the precision of the digest function has
   the advantage that a lower precision fingerprint of some data content
   is always a prefix of a higher prefix of the same content.  This
   allows higher precision fingerprints to be converted to a lower
   precision without the need for special tools.

3.  Encoding

   A UDF fingerprint for a given data object is generated by calculating
   the Binary Fingerprint Value for the given data object and type
   identifier, truncating it to obtain the desired degree of precision
   and then converting the truncated value to a representation.








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3.1.  Binary Fingerprint Value

   The binary encoding of a fingerprint is calculated using the formula:

   Fingerprint = <<Version-ID> + H (<<Content-ID>  + ?:? + H(<<Data>))

   Where

   H(x) is the cryptographic digest function
   <<Version-ID> is the fingerprint version and algorithm identifier.
   <<Content-ID> is the MIME Content-Type of the data.
   <<Data> is the binary data.

   The use of the nested hash function permits a fingerprint to be taken
   of data for which a digest value is already known without the need to
   calculate a new digest over the data.

   The inclusion of a MIME content type prevents message substitution
   attacks in which one content type is substituted for another.

3.1.1.  Version ID

   Two digest algorithm identifiers are specified in this document:

   SHA-2-512 = 96

   SHA-3-512 = 144

   These algorithm identifiers have been carefully chosen so that the
   first character in a SHA-2-512 fingerprint will always be 'M' and the
   first character in a SHA-3-512 fingerprint will always be 'S'.  These
   provide mnemonics for 'Merkle-Damgard' and 'Sponge' respectively.

3.2.  Truncation

   The Binary Fingerprint Value is truncated to an integer multiple of
   25 bits regardless of the intended output representation.

   The output of the hash function is truncated to a sequence of n bits
   by first selecting the first n/8 bytes of the output function.  If n
   is an integer multiple of 8, no additional bits are required and this
   is the result.  Otherwise the remaining bits are taken from the most
   significant bits of the next byte and any unused bits set to 0.

   For example, to truncate the byte sequence [a0, b1, c2, d3, e4] to 25
   bits. 25/8 = 3 bytes with 1 bit remaining, the first three bytes of
   the truncated sequence is [a0, b1, c2] and the final byte is e4 AND




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   80 = 80 which we add to the previous result to obtain the final
   truncated sequence of [a0, b1, c2, 80]

3.3.  Base32 Representation

   A modified version of Base32 [RFC4648] encoding is used to present
   the fingerprint in text form grouping the output text into groups of
   five characters separated by a dash '-'.  This representation
   improves the accuracy of both data entry and verification.

3.4.  URI Representation

   Any UDF fingerprint MAY be encoded as a URI by prefixing the Base32
   text representation of the fingerprint with the string 'udf:'

3.5.  Examples

   In the following examples, <Content-ID> is the UTF8 encoding of the
   string "text/plain" and is the UTF8 encoding of the string "UDF Data
   Value"

   Data = 55 44 46 20 44 61 74 61 20 56 61 6c 75 65

3.5.1.  Using SHA-2-512 Digest

   H( <Data> ) =
       48 da 47 cc  ab fe a4 5c  76 61 d3 21  ba 34 3e 58
       10 87 2a 03  b4 02 9d ab  84 7c ce d2  22 b6 9c ab
       02 38 d4 e9  1e 2f 6b 36  a0 9e ed 11  09 8a ea ac
       99 d9 e0 bd  ea 47 93 15  bd 7a e9 e1  2e ad c4 15
   H(H( <Data> ) + Content-ID>) =
       45 e0 59 e0  39 34 ea b7  f6 5d 83 b2  d8 f9 b1 6d
       2a 6b 08 63  d9 3c c1 02  86 7b 83 49  f2 d9 f0 8f
       fe 07 87 30  c7 c9 05 74  ac a1 38 2b  b3 14 4d c6
       39 f9 8c 12  c0 4a 3e b5  05 0b 3e 67  df 52 4b 57

   Text Presentation (100 bit)MB2GK-6DUF5-YGYYL-JNY5E

   Text Presentation (125 bit)MB2GK-6DUF5-YGYYL-JNY5E-RWSHZ

   Text Presentation (150bit)MB2GK-6DUF5-YGYYL-JNY5E-RWSHZ-SV75J

   Text Presentation (250bit)MB2GK-6DUF5-YGYYL-JNY5E-RWSHZ-SV75J-C4OZQ-
   5GIN2-GQ7FQ-EEHFI







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3.5.2.  Using SHA-3-512 Digest

   [This data intentionally omitted pending publication of the final
   SHA-3 standards document]

4.  Content Types

4.1.  PKIX keyInfo

4.2.  OpenPGP Key

5.  Additional UDF Renderings

   By default, a UDF fingerprint is rendered in the Base32 encoding
   described in this document.  Additional renderings MAY be employed to
   facilitate entry and/or verification of fingerprint values.

5.1.  Machine Readable Rendering

   The use of a machine readable rendering such as a QR Code allows a
   UDF value to be input directly using a smartphone or other device
   equipped with a camera.

   A QR code fixed to a network capable device might contain the
   fingerprint of a machine readable description of the device.

5.2.  Word Lists

   The use of a Word List to encode fingerprint values was introduced by
   Patrick Juola and Philip Zimmerman for the PGPfone application.  The
   PGP Word List is designed to facilitate exchange and verification of
   fingerprint values in a voice application.  To minimize the risk of
   misinterpretation, two word lists of 256 values each are used to
   encode alternative fingerprint bytes.  The compact size of the lists
   used allowed the compilers to curate them so as to maximize the
   phonetic distance of the words selected.

   The PGP Word List is designed to achieve a balance between ease of
   entry and verification.  Applications where only verification is
   required may be better served by a much larger word list, permitting
   shorter fingerprint encodings.

   For example, a word list with 16384 entries permits 14 bits of the
   fingerprint to be encoded at once, 65536 entries permits 16.  These
   encodings allow a 125 bit fingerprint to be encoded in 9 and 8 words
   respectively.





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5.3.  Image List

   An image list is used in the same manner as a word list affording
   rapid visual verification of a fingerprint value.  For obvious
   reasons, this approach is not generally suited to data entry.

6.  Security Considerations

6.1.  Precision

6.2.  Use of Truncated Digests

7.  IANA Considerations

   [This will be extended later]

7.1.  URI Registration

   [Here a URI registration for the udf: scheme]

7.2.  Content Type Registration

   [PKIX KeyInfo]

   [PGP Key Packet]

7.3.  Version Registry

   96 = SHA-2-512

   144 = SHA-3-512

8.  Normative References

   [RFC1321]  Rivest, R., "The MD5 Message-Digest Algorithm", RFC 1321,
              DOI 10.17487/RFC1321, April 1992.

   [RFC4648]  Josefsson, S., "The Base16, Base32, and Base64 Data
              Encodings", RFC 4648, DOI 10.17487/RFC4648, October 2006.

Author's Address

   Phillip Hallam-Baker
   Comodo Group Inc.

   Email: philliph@comodo.com





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