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Network Working Group D. Eastlake 3rd
Request for Comments: 3797 Motorola Laboratories
Obsoletes: 2777 June 2004
Category: Informational
Publicly Verifiable Nominations Committee (NomCom) Random Selection
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.
Copyright Notice
Copyright (C) The Internet Society (2004).
Abstract
This document describes a method for making random selections in such
a way that the unbiased nature of the choice is publicly verifiable.
As an example, the selection of the voting members of the IETF
Nominations Committee (NomCom) from the pool of eligible volunteers
is used. Similar techniques would be applicable to other cases.
Table of Contents
1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . 2
2. General Flow of a Publicly Verifiable Process . . . . . . . . . 2
2.1. Determination of the Pool . . . . . . . . . . . . . . . . 2
2.2. Publication of the Algorithm. . . . . . . . . . . . . . . 3
2.3. Publication of Selection. . . . . . . . . . . . . . . . . 3
3. Randomness. . . . . . . . . . . . . . . . . . . . . . . . . . . 3
3.1. Sources of Randomness . . . . . . . . . . . . . . . . . . 3
3.2. Skew. . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3.3. Entropy Needed. . . . . . . . . . . . . . . . . . . . . . 4
4. A Suggested Precise Algorithm . . . . . . . . . . . . . . . . . 5
5. Handling Real World Problems. . . . . . . . . . . . . . . . . . 7
5.1. Uncertainty as to the Pool. . . . . . . . . . . . . . . . 7
5.2. Randomness Ambiguities. . . . . . . . . . . . . . . . . . 7
6. Fully Worked Example. . . . . . . . . . . . . . . . . . . . . . 8
7. Security Considerations . . . . . . . . . . . . . . . . . . . . 9
8. Reference Code. . . . . . . . . . . . . . . . . . . . . . . . . 10
Appendix A: History of NomCom Member Selection . . . . . . . . . . 16
Appendix B: Changes from RFC 2777. . . . . . . . . . . . . . . . . 16
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . 17
Eastlake 3rd Informational [Page 1]
RFC 3797 Verifiable Random Selection June 2004
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Normative References. . . . . . . . . . . . . . . . . . . . . . 17
Informative References. . . . . . . . . . . . . . . . . . . . . 17
Author's Address . . . . . . . . . . . . . . . . . . . . . . . . . 18
Full Copyright Statement . . . . . . . . . . . . . . . . . . . . . 19
1. Introduction
Under the IETF rules, each year ten people are randomly selected from
among eligible volunteers to be the voting members of the IETF
nominations committee (NomCom). The NomCom nominates members of the
Internet Engineering Steering Group (IESG) and the Internet
Architecture Board (IAB) as described in [RFC 3777]. The number of
eligible volunteers in recent years has been around 100.
It is highly desirable that the random selection of the voting NomCom
be done in an unimpeachable fashion so that no reasonable charges of
bias or favoritism can be brought. This is as much for the
protection of the selection administrator (currently, the appointed
non-voting NomCom chair) from suspicion of bias as it is for the
protection of the IETF.
A method such that public information will enable any person to
verify the randomness of the selection meets this criterion. This
document gives an example of such a method.
The method, in the form it appears in RFC 2777, was also used by IANA
in February 2003 to determine the ACE prefix for Internationalized
Domain Names [RFC 3490] so as to avoid claim jumping.
2. General Flow of a Publicly Verifiable Process
A selection of NomCom members publicly verifiable as unbiased or
similar selection could follow the three steps given below.
2.1. Determination of the Pool
First, determine the pool from which the selection is to be made as
provided in [RFC 3777] or its successor.
Volunteers are solicited by the selection administrator. Their names
are then passed through the IETF Secretariat to check eligibility.
(Current eligibility criteria relate to IETF meeting attendance,
records of which are maintained by the Secretariat.) The full list
of eligible volunteers is made public early enough that a reasonable
time can be given to resolve any disputes as to who should be in the
pool.
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2.2. Publication of the Algorithm
The exact algorithm to be used, including the public future sources
of randomness, is made public. For example, the members of the final
list of eligible volunteers are ordered by publicly numbering them,
some public future sources of randomness such as government run
lotteries are specified, and an exact algorithm is specified whereby
eligible volunteers are selected based on a strong hash function
[RFC 1750] of these future sources of randomness.
2.3. Publication of Selection
When the pre-specified sources of randomness produce their output,
those values plus a summary of the execution of the algorithm for
selection should be announced so that anyone can verify that the
correct randomness source values were used and the algorithm properly
executed. The algorithm can be run to select, in an ordered fashion,
a larger number than are actually necessary so that if any of those
selected need to be passed over or replaced for any reason, an
ordered set of additional alternate selections will be available. A
cut off time for any complaint that the algorithm was run with the
wrong inputs or not faithfully executed must be specified to finalize
the output and provide a stable selection.
3. Randomness
The crux of the unbiased nature of the selection is that it is based
in an exact, predetermined fashion on random information which will
be revealed in the future and thus can not be known to the person
specifying the algorithm. That random information will be used to
control the selection. The random information must be such that it
will be publicly and unambiguously revealed in a timely fashion.
The random sources must not include anything that any reasonable
person would believe to be under the control or influence of the IETF
or its components, such as IETF meeting attendance statistics,
numbers of documents issued, or the like.
3.1. Sources of Randomness
Examples of good information to use are winning lottery numbers for
specified runnings of specified public lotteries. Particularly for
government run lotteries, great care is taken to see that they occur
on time and produce random quantities. Even in the unlikely case one
were to have been rigged, it would almost certainly be in connection
with winning money in the lottery, not in connection with IETF use.
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Other possibilities are such things as the daily balance in the US
Treasury on a specified day, the volume of trading on the New York
Stock exchange on a specified day, etc. (However, the reference code
given below will not handle integers that are too large.) Sporting
events can also be used. (Experience has indicated that stock prices
and/or volumes are a poor source of unambiguous data due trading
suspensions, company mergers, delistings, splits, multiple markets,
etc.) In all cases, great care must be taken to specify exactly what
quantities are being presumed random and what will be done if their
issuance is cancelled, delayed, or advanced.
It is important that the last source of randomness, chronologically,
produce a substantial amount of the entropy needed. If most of the
randomness has come from the earlier of the specified sources, and
someone has even limited influence on the final source, they might do
an exhaustive analysis and exert such influence so as to bias the
selection in the direction they wanted. Thus it is best for the last
source to be an especially strong and unbiased source of a large
amount of randomness such as a government run lottery.
It is best not to use too many different sources. Every additional
source increases the probability that one or more sources might be
delayed, cancelled, or just plain screwed up somehow, calling into
play contingency provisions or, worst of all, creating a situation
that was not anticipated. This would either require arbitrary
judgment by the selection administrator, defeating the randomness of
the selection, or a re-run with a new set of sources, causing much
delay. Three or four would be a good number of sources. Ten is too
many.
3.2. Skew
Some of the sources of randomness produce data that is not uniformly
distributed. This is certainly true of volumes, prices, and horse
race results, for example. However, use of a strong mixing function
[RFC 1750] will extract the available entropy and produce a hash
value whose bits, remainder modulo a small divisor, etc., deviate
from a uniform distribution only by an insignificant amount.
3.3. Entropy Needed
What we are doing is selecting N items without replacement from a
population of P items. The number of different ways to do this is as
follows, where "!" represents the factorial function:
P!
-------------
N! * (P - N)!
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To do this in a completely random fashion requires as many random
bits as the logarithm base 2 of that quantity. Some sample
calculated approximate number of random bits for the completely
random selection of 10 NomCom members from various pool sizes is
given below:
Random Selection of Ten Items From Pool
Pool size 20 25 30 35 40 50 60 75 100 120
Bits needed 18 22 25 28 30 34 37 40 44 47
Using an inadequate number of bits means that not all of the possible
sets of ten selected items would be available. For a substantially
inadequate amount of entropy, there could be a significant
correlation between the selection of two different members of the
pool, for example. However, as a practical matter, for pool sizes
likely to be encountered in IETF NomCom membership selection, 40 bits
of entropy should always be adequate. Even if there is a large pool
and more bits are needed for perfect randomness, 40 bits of entropy
will assure only an insignificant deviation from completely random
selection for the difference in probability of selection of different
pool members, the correlation between the selection of any pair of
pool members, etc.
An MD5 [RFC 1321] hash has 128 bits and therefore can produce no more
than that number of bits of entropy. However, this is more than
three times what is likely to ever be needed for IETF NomCom
membership selection. A even stronger hash, such as SHA-1
[RFC 3174], can be used if desired.
4. A Suggested Precise Algorithm
It is important that a precise algorithm be given for mixing the
random sources specified and making the selection based thereon.
Sources suggested above produce either a single positive number
(i.e., NY Stock Exchange volume in thousands of shares) or a small
set of positive numbers (many lotteries provide 6 numbers in the
range of 1 through 40 or the like, a sporting event could produce the
scores of two teams, etc.). A suggested precise algorithm is as
follows:
1. For each source producing multiple numeric values, represent
each as a decimal number terminated by a period (or with a
period separating the whole from the fractional part), without
leading zeroes (except for a single leading zero if the integer
part is zero), and without trailing zeroes after the period.
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2. Order the values from each source from smallest to the largest
and concatenate them and suffix the result with a "/". For
each source producing a single number, simply represent it as
above with a suffix "/". (This sorting is necessary because
the same lottery results, for example, are sometimes reported
in the order numbers were drawn and sometimes in numeric order
and such things as the scores of two sports teams that play a
game has no inherent order.)
3. At this point you have a string for each source, say s1/, s2/,
... Concatenate these strings in a pre-specified order, the
order in which the sources were listed if not otherwise
specified, and represent each character as its ASCII code
[ASCII] producing "s1/s2/.../".
You then produce a sequence of random values derived from a strong
mixing of these sources by calculating the MD5 hash [RFC 1321] of
this string prefixed and suffixed with an all zeros two byte sequence
for the first value, the string prefixed and suffixed by 0x0001 for
the second value, etc., treating the two bytes as a big endian
counter. Treat each of these derived "random" MD5 output values as a
positive 128-bit multiprecision big endian integer.
Then totally order the pool of listed volunteers as follows: If there
are P volunteers, select the first by dividing the first derived
random value by P and using the remainder plus one as the position of
the selectee in the published list. Select the second by dividing
the second derived random value by P-1 and using the remainder plus
one as the position in the list with the first selected person
eliminated. Etc.
It is STRONGLY recommended that alphanumeric random sources be
avoided due to the much greater difficulty in canonicalizing them in
an independently repeatable fashion; however, if you choose to ignore
this advice and use an ASCII or similar Roman alphabet source or
sources, all white space, punctuation, accents, and special
characters should be removed and all letters set to upper case. This
will leave only an unbroken sequence of letters A-Z and digits 0-9
which can be treated as a canonicalized number above and suffixed
with a "./". If you choose to not just ignore but flagrantly flout
this advice and try to use even more complex and harder to
canonicalize internationalized text, such as UNICODE, you are on your
own.
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5. Handling Real World Problems
In the real world, problems can arise in following the steps and flow
outlined in Sections 2 through 4 above. Some problems that have
actually arisen are described below with recommendations for handling
them.
5.1. Uncertainty as to the Pool
Every reasonable effort should be made to see that the published pool
from which selection is made is of certain and eligible persons.
However, especially with compressed schedules or perhaps someone
whose claim that they volunteered and are eligible has not been
resolved by the deadline, or a determination that someone is not
eligible which occurs after the publication of the pool, it may be
that there are still uncertainties.
The best way to handle this is to maintain the announced schedule,
INCLUDE in the published pool all those whose eligibility is
uncertain and to keep the published pool list numbering IMMUTABLE
after its publication. If someone in the pool is later selected by
the algorithm and random input but it has been determined they are
ineligible, they can be skipped and the algorithm run further to make
an additional selection. Thus the uncertainty only effects one
selection and in general no more than a maximum of U selections where
there are U uncertain pool members.
Other courses of action are far worse. Actual insertion or deletion
of entries in the pool after its publication changes the length of
the list and totally scrambles who is selected, possibly changing
every selection. Insertion into the pool raises questions of where
to insert: at the beginning, end, alphabetic order, ... Any such
choices by the selection administrator after the random numbers are
known destroys the public verifiability of fair choice. Even if done
before the random numbers are known, such dinking with the list after
its publication just smells bad. There should be clear fixed public
deadlines and someone who challenges their absence from the pool
after the published deadline should have their challenge
automatically denied for tardiness.
5.2. Randomness Ambiguities
The best good faith efforts have been made to specify precise and
unambiguous sources of randomness. These sources have been made
public in advance and there has not been objection to them. However,
it has happened that when the time comes to actually get and use this
randomness, the real world has thrown a curve ball and it isn't quite
clear what data to use. Problems have particularly arisen in
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connection with stock prices, volumes, and financial exchange rates
or indices. If volumes that were published in thousands are
published in hundreds, you have a rounding problem. Prices that were
quoted in fractions or decimals can change to the other. If you take
care of every contingency that has come up in the past, you can be
hit with a new one. When this sort of thing happens, it is generally
too late to announce new sources, an action which could raise
suspicions of its own. About the only course of action is to make a
reasonable choice within the ambiguity and depend on confidence in
the good faith of the selection administrator. With care, such cases
should be extremely rare.
Based on these experiences, it is again recommended that public
lottery numbers or the like be used as the random inputs and stock
prices and volumes avoided.
6. Fully Worked Example
Assume the following ordered list of 25 eligible volunteers is
published in advance of selection:
1. John 11. Pollyanna 21. Pride
2. Mary 12. Pendragon 22. Sloth
3. Bashful 13. Pandora 23. Envy
4. Dopey 14. Faith 24. Anger
5. Sleepy 15. Hope 25. Kasczynski
6. Grouchy 16. Charity
7. Doc 17. Lee
8. Sneazy 18. Longsuffering
9. Handsome 19. Chastity
10. Cassandra 20. Smith
Assume the following (fake example) ordered list of randomness
sources:
1. The Kingdom of Alphaland State Lottery daily number for 1 November
2004 treated as a single four digit integer.
2. Numbers of the winning horses at Hialeia for all races for the
first day on or after 13 October 2004 on which at least two races
are run.
3. The People's Democratic Republic of Betastani State Lottery six
winning numbers (ignoring the seventh "extra" number) for 1
November 2004.
Hypothetical randomness publicly produced:
Source 1: 9319
Source 2: 2, 5, 12, 8, 10
Source 3: 9, 18, 26, 34, 41, 45
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Resulting key string:
9319./2.5.8.10.12./9.18.26.34.41.45./
The table below gives the hex of the MD5 of the above key string
bracketed with a two byte string that is successively 0x0000, 0x0001,
0x0002, through 0x0010 (16 decimal). The divisor for the number size
of the remaining pool at each stage is given and the index of the
selectee as per the original number of those in the pool.
index hex value of MD5 div selected
1 990DD0A5692A029A98B5E01AA28F3459 25 -> 17 <-
2 3691E55CB63FCC37914430B2F70B5EC6 24 -> 7 <-
3 FE814EDF564C190AC1D25753979990FA 23 -> 2 <-
4 1863CCACEB568C31D7DDBDF1D4E91387 22 -> 16 <-
5 F4AB33DF4889F0AF29C513905BE1D758 21 -> 25 <-
6 13EAEB529F61ACFB9A29D0BA3A60DE4A 20 -> 23 <-
7 992DB77C382CA2BDB9727001F3CDCCD9 19 -> 8 <-
8 63AB4258ECA922976811C7F55C383CE7 18 -> 24 <-
9 DFBC5AC97CED01B3A6E348E3CC63F40D 17 -> 19 <-
10 31CB111C4A4EBE9287CEAE16FE51B909 16 -> 13 <-
11 07FA46C122F164C215BBC72793B189A3 15 -> 22 <-
12 AC52F8D75CCBE2E61AFEB3387637D501 14 -> 5 <-
13 53306F73E14FC0B2FBF434218D25948E 13 -> 18 <-
14 B5D1403501A81F9A47318BE7893B347C 12 -> 9 <-
15 85B10B356AA06663EF1B1B407765100A 11 -> 1 <-
16 3269E6CE559ABD57E2BA6AAB495EB9BD 10 -> 4 <-
Resulting first ten selected, in order selected:
1. Lee (17) 6. Envy (23)
2. Doc (7) 7. Sneazy (8)
3. Mary (2) 8. Anger (24)
4. Charity (16) 9. Chastity (19)
5. Kasczynski (25) 10. Pandora (13)
Should one of the above turn out to be ineligible or decline to
serve, the next would be Sloth, number 22.
7. Security Considerations
Careful choice of should be made of randomness inputs so that there
is no reasonable suspicion that they are under the control of the
administrator. Guidelines given above to use a small number of
inputs with a substantial amount of entropy from the last should be
followed. And equal care needs to be given that the algorithm
selected is faithfully executed with the designated inputs values.
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Publication of the results and a week or so window for the community
of interest to duplicate the calculations should give a reasonable
assurance against implementation tampering.
8. Reference Code
This code makes use of the MD5 reference code from [RFC 1321] ("RSA
Data Security, Inc. MD5 Message-Digest Algorithm"). The portion of
the code dealing with multiple floating point numbers was written by
Matt Crawford. The original code in RFC 2777 could only handle pools
of up to 255 members and was extended to 2**16-1 by Erik Nordmark.
This code has been extracted from this document, compiled, and
tested. While no flaws have been found, it is possible that when
used with some compiler on some system some flaw will manifest
itself.
/****************************************************************
*
* Reference code for
* "Publicly Verifiable Random Selection"
* Donald E. Eastlake 3rd
* February 2004
*
****************************************************************/
#include <limits.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
/* From RFC 1321 */
#include "global.h"
#include "MD5.h"
/* local prototypes */
int longremainder ( unsigned short divisor,
unsigned char dividend[16] );
long int getinteger ( char *string );
double NPentropy ( int N, int P );
/* limited to up to 16 inputs of up to sixteen integers each */
/* pool limit of 2**8-1 extended to 2**16-1 by Erik Nordmark */
/****************************************************************/
main ()
{
int i, j, k, k2, err, keysize, selection, usel;
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unsigned short remaining, *selected;
long int pool, temp, array[16];
MD5_CTX ctx;
char buffer[257], key [800], sarray[16][256];
unsigned char uc16[16], unch1, unch2;
pool = getinteger ( "Type size of pool:\n" );
if ( pool > 65535 )
{
printf ( "Pool too big.\n" );
exit ( 1 );
}
selected = (unsigned short *) malloc ( (size_t)pool );
if ( !selected )
{
printf ( "Out of memory.\n" );
exit ( 1 );
}
selection = getinteger ( "Type number of items to be selected:\n" );
if ( selection > pool )
{
printf ( "Pool too small.\n" );
exit ( 1 );
}
if ( selection == pool )
printf ( "All of the pool is selected.\n" );
else
{
err = printf ( "Approximately %.1f bits of entropy needed.\n",
NPentropy ( selection, pool ) + 0.1 );
if ( err <= 0 ) exit ( 1 );
}
for ( i = 0, keysize = 0; i < 16; ++i )
{
if ( keysize > 500 )
{
printf ( "Too much input.\n" );
exit ( 1 );
}
/* get the "random" inputs. echo back to user so the user may
be able to tell if truncation or other glitches occur. */
err = printf (
"\nType #%d randomness or 'end' followed by new line.\n"
"Up to 16 integers or the word 'float' followed by up\n"
"to 16 x.y format reals.\n", i+1 );
if ( err <= 0 ) exit ( 1 );
gets ( buffer );
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j = sscanf ( buffer,
"%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld%ld",
&array[0], &array[1], &array[2], &array[3],
&array[4], &array[5], &array[6], &array[7],
&array[8], &array[9], &array[10], &array[11],
&array[12], &array[13], &array[14], &array[15] );
if ( j == EOF )
exit ( j );
if ( !j )
if ( buffer[0] == 'e' )
break;
else
{ /* floating point code by Matt Crawford */
j = sscanf ( buffer,
"float %ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]"
"%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]"
"%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]"
"%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]%ld.%[0-9]",
&array[0], sarray[0], &array[1], sarray[1],
&array[2], sarray[2], &array[3], sarray[3],
&array[4], sarray[4], &array[5], sarray[5],
&array[6], sarray[6], &array[7], sarray[7],
&array[8], sarray[8], &array[9], sarray[9],
&array[10], sarray[10], &array[11], sarray[11],
&array[12], sarray[12], &array[13], sarray[13],
&array[14], sarray[14], &array[15], sarray[15] );
if ( j == 0 || j & 1 )
printf ( "Bad format." );
else {
for ( k = 0, j /= 2; k < j; k++ )
{
/* strip trailing zeros */
for ( k2=strlen(sarray[k]); sarray[k][--k2]=='0';)
sarray[k][k2] = '\0';
err = printf ( "%ld.%s\n", array[k], sarray[k] );
if ( err <= 0 ) exit ( 1 );
keysize += sprintf ( &key[keysize], "%ld.%s",
array[k], sarray[k] );
}
keysize += sprintf ( &key[keysize], "/" );
}
}
else
{ /* sort values, not a very efficient algorithm */
for ( k2 = 0; k2 < j - 1; ++k2 )
for ( k = 0; k < j - 1; ++k )
if ( array[k] > array[k+1] )
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{
temp = array[k];
array[k] = array[k+1];
array[k+1] = temp;
}
for ( k = 0; k < j; ++k )
{ /* print for user check */
err = printf ( "%ld ", array[k] );
if ( err <= 0 ) exit ( 1 );
keysize += sprintf ( &key[keysize], "%ld.", array[k] );
}
keysize += sprintf ( &key[keysize], "/" );
}
} /* end for i */
/* have obtained all the input, now produce the output */
err = printf ( "Key is:\n %s\n", key );
if ( err <= 0 ) exit ( 1 );
for ( i = 0; i < pool; ++i )
selected [i] = (unsigned short)(i + 1);
printf ( "index hex value of MD5 div selected\n" );
for ( usel = 0, remaining = (unsigned short)pool;
usel < selection;
++usel, --remaining )
{
unch1 = (unsigned char)usel;
unch2 = (unsigned char)(usel>>8);
/* prefix/suffix extended to 2 bytes by Donald Eastlake */
MD5Init ( &ctx );
MD5Update ( &ctx, &unch2, 1 );
MD5Update ( &ctx, &unch1, 1 );
MD5Update ( &ctx, (unsigned char *)key, keysize );
MD5Update ( &ctx, &unch2, 1 );
MD5Update ( &ctx, &unch1, 1 );
MD5Final ( uc16, &ctx );
k = longremainder ( remaining, uc16 );
/* printf ( "Remaining = %d, remainder = %d.\n", remaining, k ); */
for ( j = 0; j < pool; ++j )
if ( selected[j] )
if ( --k < 0 )
{
printf ( "%2d "
"%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X%02X "
"%2d -> %2d <-\n",
usel+1, uc16[0],uc16[1],uc16[2],uc16[3],uc16[4],uc16[5],uc16[6],
uc16[7],uc16[8],uc16[9],uc16[10],uc16[11],uc16[12],uc16[13],
uc16[14],uc16[15], remaining, selected[j] );
selected[j] = 0;
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break;
}
}
printf ( "\nDone, type any character to exit.\n" );
getchar ();
return 0;
}
/* prompt for a positive non-zero integer input */
/****************************************************************/
long int getinteger ( char *string )
{
long int i;
int j;
char tin[257];
while ( 1 )
{
printf ( string );
printf ( "(or 'exit' to exit) " );
gets ( tin );
j = sscanf ( tin, "%ld", &i );
if ( ( j == EOF )
|| ( !j && ( ( tin[0] == 'e' ) || ( tin[0] == 'E' ) ) )
)
exit ( j );
if ( ( j == 1 ) &&
( i > 0 ) )
return i;
} /* end while */
}
/* get remainder of dividing a 16 byte unsigned int
by a small positive number */
/****************************************************************/
int longremainder ( unsigned short divisor,
unsigned char dividend[16] )
{
int i;
long int kruft;
if ( !divisor )
return -1;
for ( i = 0, kruft = 0; i < 16; ++i )
{
kruft = ( kruft << 8 ) + dividend[i];
kruft %= divisor;
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}
return kruft;
} /* end longremainder */
/* calculate how many bits of entropy it takes to select N from P */
/****************************************************************/
/* P!
log ( ----------------- )
2 N! * ( P - N )!
*/
double NPentropy ( int N, int P )
{
int i;
double result = 0.0;
if ( ( N < 1 ) /* not selecting anything? */
|| ( N >= P ) /* selecting all of pool or more? */
)
return 0.0; /* degenerate case */
for ( i = P; i > ( P - N ); --i )
result += log ( i );
for ( i = N; i > 1; --i )
result -= log ( i );
/* divide by [ log (base e) of 2 ] to convert to bits */
result /= 0.69315;
return result;
} /* end NPentropy */
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Appendix A: History of NomCom Member Selection
For reference purposes, here is a list of the IETF Nominations
Committee member selection techniques and chairs so far:
YEAR CHAIR SELECTION METHOD
1993/1994 Jeff Case Clergy
1994/1995 Fred Baker Clergy
1995/1996 Guy Almes Clergy
1996/1997 Geoff Huston Spouse
1997/1998 Mike St.Johns Algorithm
1998/1999 Donald Eastlake 3rd RFC 2777
1999/2000 Avri Doria RFC 2777
2000/2001 Bernard Aboba RFC 2777
2001/2002 Theodore Ts'o RFC 2777
2002/2003 Phil Roberts RFC 2777
2003/2004 Rich Draves RFC 2777
Clergy = Names were written on pieces of paper, placed in a
receptacle, and a member of the clergy picked the NomCom members.
Spouse = Same as Clergy except chair's spouse made the selection.
Algorithm = Algorithmic selection based on similar concepts to those
documented in RFC 2777 and herein.
RFC 2777 = Algorithmic selection using the algorithm and reference
code provided in RFC 2777 (but not the fake example sources of
randomness).
Appendix B: Changes from RFC 2777
This document differs from [RFC 2777], the previous version, in three
primary ways as follows:
(1) Section 5, on problems actually encountered with using these
recommendations for selecting an IETF NomCom and on how to handle
them, has been added.
(2) The selection algorithm code has been modified to handle pools of
up to 2**16-1 elements and the counter based prefix and suffix
concatenated with the key string before hashing has been extended
to two bytes.
(3) Mention has been added that the algorithm documented herein was
used by IANA to select the Internationalized Domain Name ACE
prefix and some minor wording changes made.
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(4) References have been divided into Informative and Normative.
(5) The list in Appendix A has been brought up to date.
Acknowledgements
Matt Crawford and Erik Nordmark made major contributions to this
document. Comments by Bernard Aboba, Theodore Ts'o, Jim Galvin,
Steve Bellovin, and others have been incorporated.
References
Normative References
[ASCII] "USA Standard Code for Information Interchange", X3.4,
American National Standards Institute: New York, 1968.
[RFC 1321] Rivest, R., "The MD5 Message-Digest Algorithm", RFC 1321,
April 1992.
[RFC 1750] Eastlake, 3rd, D., Crocker, S. and J. Schiller,
"Randomness Recommendations for Security", RFC 1750,
December 1994.
[RFC 3174] Eastlake, 3rd, D. and P. Jones, "US Secure Hash Algorithm
1 (SHA1)", RFC 3174, September 2001.
Informative References
[RFC 3777] Galvin, J., "IAB and IESG Selection, Confirmation, and
Recall Process: Operation of the Nominating and Recall
Committees", BCP 10, RFC 3777, April 2004.
[RFC 2777] Eastlake, 3rd, D., "Publicly Verifiable Nomcom Random
Selection", RFC 2777, February 2000.
[RFC 3490] Falstrom, P., Hoffman, P. and A. Costello,
"Internationalizing Domain Names in Applications (IDNA)",
RFC 3490, March 2003.
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Author's Address
Donald E. Eastlake, 3rd
Motorola Laboratories
155 Beaver Street
Milford, MA 01757 USA
Phone: +1-508-786-7554(w)
+1-508-634-2066(h)
EMail: Donald.Eastlake@motorola.com
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Full Copyright Statement
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to the rights, licenses and restrictions contained in BCP 78, and
except as set forth therein, the authors retain all their rights.
This document and the information contained herein are provided on an
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