VMs: Re: Making a vms with meaning (long)

["Jeff" <jeff@xxxxxxxxxxxxxxxxxxxxxx>]

From: "Gabriel Landini" <G.Landini@xxxxxxxxxx>
Sent: 27 June 2004 15:38


> Hi,
> I have been thinking about Gordon Rugg's "solution" for some time now. For
> sure it is an interesting method to generate nonsense, but I am not
convinced
> that it logically follows that the vms is (or could be) a hoax of that
type.
>
> Although he has shown one method of generating something like the real
thing,
> it still has to be shown that:
> 1) any statistical properties are in fact, similar to the vms, and
> 2) how likely is one to come up with grilles that produce so much text
showing
> the degree of consistency seen in the vms.
>
> Note that Gordon is aware that one needs several grilles to make something
as
> big as the vms (otherwise it starts repeating). He is surely reverse-
> engineering the grilles, to fit the vms. However extrapolating to a
possible
> hoaxer, it assumes that s/he was intending to make something like the vms
> with a large degree of consistency throughout the grilles. To end up with
a
> set of grilles like that, I think, may be difficult to achieve without a
> clear idea of where the grille cuts are to be made).
> What I mean is that (i think) it would be quite unlikely to end up with
many
> grilles that all produce vms-like text, unless you knew what one is
intending
> to produce.
>
>
> So I decided to give some hammering to the 'hoax assumption' ("it has not
been
> read because there is nothing to be read") by producing something that
looks
> and has similar properties to the vms, AND has meaning AND is difficult to
> crack.
> The method of encoding I used is simple, straightforward and perhaps time
> consuming. Decoding by the author may be relatively difficult (certainly
it
> is possible to read back, I am not sure as it could be real time read,
> perhaps not) but cracking by a third party it in its entirety is (I think)
> *quite* difficult.
>
> Here is some text block cut randomly from the encoded corpus:
>
>  otal oldar chor lkeedol eer ol dair chedy daiin ockhdar cpheol chedy
>  xar qokaiin y chedy kshdy ololdy aiin char y okeey oldar qokaiin lsho
>  daiin olsheam qoeey chedy dchos pshedaiin shedy d qol key sheol or
>  cpheeedol qokedy qokaiin daiin cthosy chedy ar aiir chedy teeol aiin
>  cheey y cheam oky qokaiin daldaiin loiii ar shtchy chedy aldaiin
>  ydchedy daiin shd okaiin qokain daiin qotcho chedy daiin lchy oloro
>
> I produced a text of similar size of the vms with this entropy statistics
on
> the first 32000 characters using Monkey:
> NewText vms
> h0 4.70044 4.64386
> h1 3.85988 3.82127
> h2 2.02343 2.14011
>
> and it follows Zipf's law AND it has a meaning.
> I can send the text who whoever wishes to have a look.
>
> I thought of leaving this as a puzzle for the list to solve, but maybe it
is
> better to tell how it was made, so even knowing the method, one realises
that
> it may be quite difficult to crack it.
>
> I used a nomenclator to exchange the words for something artificial. I
used
> vms words in their ranking order to exchange the plain text (PT) words. So
> the most common PT word is the most common vms word and so on. Therefore
all
> character-derived statistics are due to the rules of construction of vms
> words and little to do with the language (since most languages follow
Zipf's
> law). Entropy is left almost unchanged, and Zipf's law is exactly the same
as
> in the original PT.
> I imagined the author creating a two-way dictionary of imaginary
words --that
> correspond unambiguously to real words-- as he writes the vms.
>
> You do not know neither the PT source nor the language.
> Any suggestions on how to crack this *in full*?
>
> Cheers,
>
> Gabriel
>

I would visit the author, take him out to the nearest inn and get him blind
drunk. Then I would start praising him profusely on his skill in deceiving
the list. Hopefully the answer would then be disclosed.

Jeff


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