I 

1. 

. REF ID:A60419 

. Machine Identification of Words 

- .If mo~_:t or the letters or a simple substitution cryptogram. 

have· been d.~tel1$1~d there may be several possibilities ror those words 

which. C?llWin unidentified letters. For examp1e1 we may have the word . . . -- N E • T , with substitutes f'ound for all the letters except S and w. The 

correct choic~ w:tU usually present no problems to the human cryptanalyst, 

- ·. 

but would be rather d:if'ficu1t for a ma.chine. The .following suggestion is 

proposed as a fi~t f'alterlng step in the direction of doing this by machine. 

Assume each word stored in the machine has associated w.Lth it 

a symbol showing the category or field in which it is likely to occur. 

Most of' the words will have a general symbol meaning that they could occur in almost any field. When a cryptogram has been solved as tar as possible, it is broken up into word lengths by the method described in the 

attached 'Machine Separation or Words' • Then the text is scanned for incomplete words and these fragments are compared with the words in the 

machine's dictionary .f'or possible words these fragments may represent 

(taking into account the .fact that all missing letters must be found 

among the set of 1etters still unidentified). Ii' only one such word can 

be found it is printed out at this po:ln.t and the new letters so found 

added 1n other places in the message if they occur. If' two or more words 

are found which might f'it at this point, a frequency count or the category 

symbols o.f the other words or the message is taken and compared with the 

category symbols of the candidate words. The word with the symbol hav.i.ng 

the highest frequency (except the general symbol) is taken as the text 

word. 

@'pproved for Release by NSA on 09-06-2013 pursuantto E.O. 1352e 
REF ID :A6.0419 

As an example, suppose we have the following message : 

TO COMMANDER SECOND ARMY ENEMY PATROLS 

HAVE PENETRATED OUR RIGHT .LANK TO A 

TWO MILE DEPTH 

The word • L A N K , 'With B1 F 1 J 1 Q1 X and Z still unidentified might be 

B LA N K (Gen.) or FL AN K (Mi1.). On counting the category s:ymbols1 

the machine .finds 4 words from the Military categor.v and 12 words from the 

General category. It therefore selects F LAN K as the correct mrd. 

This is an extremely simple illustration. The number 

of categories may have to be increased greatly, the words in the General 

category may have to be arranged in several ways 1 provision may have to be 

made f'or using pairs or consecutive words or groups or longer length, etc. 

~· 
REF ID:A60419 

Machine Separation or Words 

Assume a machine has stored in it a dictionary of' the most 

common words in a particular type of trattic, and a set of' instructions 

as follows : Take the first letter of' the message and look through the 

dictionary to see whether there is a word beginning with this 1etter. If 

there is, proceed to the second letter. If there is a word in the dictionary beginning with these two letters proceed to the third letter, etc. 

Also note at ewry point whether the letters up to this point represent a 

complete word. It' there is a complete word in the dictionary- corresponding 

to the first r letters and no word beginning with letters l to r + l, print 

out the word represented by letters l to r and repeat the same process beginning with the ( r + l)st letter. If' there are words beginning w.i. th letters k to k+ r (but not a complete word), and no word beginning with letters k to k + r + 1, go back to the last complete word which has not been 

used and repeat the process. 

As an example suppose we have the message .A T .A N' K E R F L 

YIN'GTHEFINN'ISHFLAGWASSIGHTEDATZEROSEV 

E N H U N D R E D • Let the symbol x mean •no word beg~ ~ 

letters is in the dictionary, go back to last complete woro,t • mean •a 

word beginning with these letters is in the dictionary, proceed to next 

letter, ' o mean 'this is a complete word, proceed to next letter•. The 

various steps in dividing this message into word lengths wou1d then ___ ap~ 

~--~-~ 

;' 

pear as .follows : 

_/ 
- REF ID:A60419 

1 A 0 

2 AT 0 

3 ATA x 

4 AT A 0 

, AT AN 0 

6 AT ANK x 

7 AT AN K • 8 AT AN KE • 

9 AT AN KER x 

10 AT AN • 

11 AT A NK x 

12 AT • 

13 A TA • 14 A TAN 0 

15 A TANK 0 

16 A TANKE • 17 A TANKER 0 

18 A TANKERF x 

19 A TANKER F • 20 A TANKER FL • 

21 A TANKER FLY 0 

22 A TANKER FLYI • 

23 A TANKER FLYIN • 

24 A TANKER FLYING 0 

25 A TANKER FLYmGT x 

26 A TANKER FLYING T • 

The number of steps could be slightly reduced by using 

some miscellaneous instructions such as requiring that if a complete word 

at any point is AN, the next word must begin with a vowel. In the example 

above, steps 8 and 9 would be eliminated by this instruction. However it 

would probably not be worth while using any instructions except those which 

refer to words in the dictionary. 

There will occasionally be a word :in the message which 

is not in the dictionary. In that case the machine would have to be instructed to go back in tum to each one of the complete words which had 

not been used and begin again from there. If no sequence of words can be 

found by regrouping the letters up to this point, the machine would print 

- . 
REF ID:A60419 

out the words up to the inadmissible word and the next letter separately 

and then proceed as though this were the beginning ot a new mwssage • For 

I 4 

example 11 suppose the word Finnish :i.n the message given were not :Ln the 

dictionary. The machine steps would then appear as on the sheet attached. 

At step h4 all the complete words have been tried without success. Theretore A TANKER FLYING THE F is printed out and the remainder treated like 

a new message. The same situation arises at step 48. Here, however, the 

machine can go back only to step 4~ in its search for compl.ete words. The 

onk possibility is IN at step 46. The ma.chine tries INN, IN NI and INNIS 

At this point there is no word in the dictionary beginning with NIS.,an.d no 

complete word still untried. Therefore the machine prints out IN N and goes 

on to I, IS and ISH. Eventually it gets to F, F.L, FLl'11 FLAG, etc. an.d from 

here on it is clear sai.ling. 

The final version is A TANKER FLYING THE F IN NIS 

H ~G WAS SIGHTED AT ZEROS EVEN HUNDRED. 

Note that the machine would print out ZEROS EVIiN 

instead of ZERO SEVEN11 since it will always take the longest possible word. 

The ma.chine might be instrncted to scan the finished product for all complete words which have not been used. These may be broken up in different 

ways and scores for pairs of consecutive words calcula.i>ed. I.f, for example, 

the tina1 version contained the three consecutive words WILL BEAT ZERO ••• 

the machine would already have noted that BE is a complete word in the 

dictionary, and on breaking BEAT at BE, the machine would also note that 

AT is another complete word :in the dictionary. It would then compare 

WILL BEAT ZERO with WILL BE AT ZERO. WILL BE will score higher than WILL 

BEAT and AT ZERO will score higher than BEAT ZERO. Therefore the text 

will be changed to WILL BE AT ZERO • • • 
REF ID.:A60419 
f ..... 

. +, 1 ~ 

i "f - ... . . 

I 

. -.. . + 

·~ 

I 
. - -- . REF ID:A60419 

MEMORANDUM 

SUBJECT: Suggested Means for Increased Automation in C~yp~ana.J.ys;s • 

l. GENERAL -........ .. 

In normal written alphabetic language there is.~a spatial relationship between and among contiguous letters, particularly as regards the 

vowels and consonants, which enables the mind to recognize almos~ iristantan- .. . .. -

eously upon the receipt of visual impulses from the eyes a feature of s~ch 

---i·~-~ ... :.•-~--:-~· .. -.-:~ ·P'--i\" 

a language which we call pronounceability. It is iiry belief ·that~the -pro- - _: ~ .;, ~ .i -: ., ~ .. ,, ... • .i ~ • 

.. - • . .... .!!'.,,,...,,,... 

nounceability phenomenon is what the mind apprehends Qr_ recognizes fir~t .:- ...... ~ - -!,•- -

of all and long before the succession or constellatio~s·or letters forming ... - ..• ,, .. •t'"""' f 

words are recognized as words and the latter become ~ntelligible~ What 

we need to know more about is this phenomenon of pronounceability and how 

the mind or brain apprehends it. The phenomenon is probably basically 

- electrical in nature and the problem then is to design a ma.chine that will 

simulate whatever electrical process takes place in the brain, a process 

which perhaps corresponds to the phenomenon in question. This, I believe, 

·would not be too difficult and I conceive of a complex of components which 

would be of the nature described and would operate as a system in the 

:rranner described below: 

2. PROCEDURE 

a. Assume we are dealing with a cryptographic version of a text 

of 100 or more letters of good normal English which has been enciphered 

monoalphabetically by a random-mixed alphabet. Assume a ma.chine of the 

digital computer type, into which impulses {in a binary code) corresponding 

to the succession of the letters or characters of the cipher text are fed, 

by the usual means {punched cards, perforated pa.per or magnetic tape, or the 

like) as the input. 
-- ·- ;. •.J' 

REF ID:A60419 

b. The first step for the ma.chine, on acceptance of the input, 

would be to program its functioning, according to the usual methods, to 

conduct the impulses to and store them in the memory, making at the 

same time and storing a unilateral frequency count of the characters of 

the cipher text. The ma.chine then determines the 10 cipher letters most 

frequently represented and sets them up in a descending order of frequency. 

c. The ma.chine's next operation is to set up lo'! permutations of 

equivalents, beginning with the permutation corresponding to the normal 

English frequency expectancy series E1 T1 01 A1 I,N, R1 5 1 H, D. The 

substitution equivalents of the first of these 10! permutations are then 

applied by the machine to the appropriate letters of the cipher text and 

at the same time impulses which will trigger off signals corresponding to 

and capable of ma.king sound spectographic representations of the substitutional 

plain-text equivalents are set up within the machine and temporarily impressed 

upon a mediwn capable of being moved laterally (film, magnetic tape, etc.) 

past a sound-spectograph reading component. 

d. The sound-producing component of the machine, actuated by the 

reading component, 11 pronounces 11 the sequence of spectographic representations 

or, at least, it attempts to do so as best it c~n: The ma.chine, fUrtherm.ore, • 

is set so that there is a lower threshold-of 11 ~onounpe~bility, 11 ;,,hich unless 

' ' 

reached and passed, will cause a "stuttering" or somi;; phenomenon equivalent to 

a "lingual impediment. 11 When the ma.chine finds the imPediment beyond the ,. r • - ...... I'~ 

threshold or critical value of pronounceability -- in other words, when what it - ~- .... 

tries to enunciate is "unpronounceable" in English-:- it_t_l:p:-ows out the permutation • • ... .r.. : 

selected and begins to repeat its sequence Jf ope!~t!~n4 c;~_~the' n~~{ ~f'~the 10! 

. ,.. ! ' .-: .t ~ .· •. I .:,. "'~.:a -· .:: .... permutations. -: ;;. .;. -;. 1 -~. \ .~.,. ·.:.:---- • 

..., --

• 
. ~ 

REF ID:A60419 

e. The ma.chine should be able in this way to eliminate a great many of 

the 10! permutations at a very rapid rate, retaining only a few which surpass 

the critical threshold of 11 pronounceability11 • These remaining possibilities 

will have to be examined visually or "listened to" by the operator. 

f. Assuming the correct permutation of the 10! high frequency 

letters has been isolated the analyst will certainly be able to fill in the 

remaining letters without too much difficulty. 

.. . . 

.. . ii ... ~r,.'f • -l .. , ., • 

.,, .. ¥. -

.. ·- .... - ~ 

J;,,J t.11 r ..., 

- f,f ,~~:;;. 1-~ 

• ":I"': • ... --;"" _--.. • -~ -

... :.J :1'-" .. 

-.... 

-} 

. ...... . ) 

.. " .. 

. - I 

··~ ·: 
------R-:E .... E-ID..:.A6.0A ....-'--------------

nounceab:llity phenomenon ia Ybat the mind appreheud.e or recognises f'irat 

o"t all a.tld. long betora the aucce111on or constellations ot letters tormilJg 

vorda are :recognized .alJ 'W'Ords ~ the lat.ter beconp iu.tell1g1ble. What 

we need to know more about i• th1• phenomenon or pronounceab:111t:y and how 

the mind or brain a~ehenda it. ~ Pienomenon is proba.b~ baaical~ 

electrical in nature and. the problem then ia to design & machine that 'dU 

aimul&te whatever electrical precess takes pl.ace in the brain, a process I 

which perhaps correaponds to the phenomenon in ql.\eetion. 'l'hie, I believe, 

would not be too dif'ticul.t an4 :t conceive ot a com;plex ot components which 

vould. be of the nature deacribecl emd. 1t0ul4 operate a.a e. 1yatem. in the 

manner described bel.Ov'a 

a. JIROCBJ>tJRI I 

I ' • 

•• Aseume. we ~ dealiila with a cr)'Ptasraph!c version ot a text I _, 

I 

ot 100 or more letters at good nor.ual Jlngliah which has 'been enciphered I 

moncalphabetical~ by .~ ~ .. mixed alphabet. .Aawma a •chine ot the I 

41s1ta.J. com:pJ.ter/~~ into which :!mPlllaea (in a binary code) eorreaponding 

to the auace•a1on ot the letters or cnaracter• ot the cipher text are ted, I .I • I 

by the usual. -~ (punched oar4a1 pertorated paper or magnetic tape, or the 

111.f.c) •• lbe ~~i;. ~ 

• i f 

Ii 

I .. - - . 

I -·-1--- , 

i 

'· i\ 

I \ 

\ 

i \1 

-f>*~ 

I ( .:='.;..,,'',. 
REF ID:A60419 

b. 1!le tirat atep t<r the -.chine, on acceptance Of the inpUt, 

voulc:l be to progl'Ul ita tun.cti®ina, accOl"d.iDg to ~ uaual •thod.B, to 

conduct the ~sea to and. atore them in the ~' •kjng at the 

•a.me tiJDa Q4. 1tor1r>,g a unilateral .t:requenc:;r count ot tbe characters c4 

the cipher text,. 'rhe me.chine then determinea the 10 cipher letters most 

frequently repreeented and Hta thelll up in a descend.ing order or frequency. 

c. !l'he ma.chine'• next operation is to eet up l0?-permutat1ona ot 

•!iuival.enta, beginning with the p&l'mUtation corresp:mding to the normal 

!ngl:l1h t'requency e~pec.ta.ncy aeries E1 T, O, A, X,,Jr,, R, 11 B, :o. The 

•ub•titution equivalents ot tbe 1'1.rst ot these lO! permutations are then 

applied b;y the :me.chine to the &pprOIJriate letters ot the cipher text ~ 

at the sa.me tim 1mpulaea whiah will tr!66er ott •1.grmJ.• corresp:mdi:pg to 

and cape.ble ot making aound apectograpbic representations or tho aub1t1tu.t10Dal 

plain-text eQ.uivalenta are aet up Yitb.U;i the :oachina and. temporari.lf impreaaod 

upcm a medium ce.xiablo ot being moved. later~ (tilm, magnetic te.pe1 •te:J.) 

past a •ound-•pectograph readil'Jg component .. 

4. ~Jle •oWld-produaillg cOZ!lpO.nent ot the DB.chine, aotuat~d by the 

\ ree.diDg component, "pronounces" the •eq,u.en~e d apeatograpbic rep-eaentat10ll8 

\\ 

-- or; at least, it attempts to do 10 as beat it can. The na.chine1 turtherll¥)l'81 \ 1 

\}\ 

1• 1et so that there it a lQVQ.r threshold ot "prol10W1Ceabil1ty, 11 vhioh unl.e11 ·, \ : 

l \ 

reached and p1.aaed,, vill eauee a "istuttering'' or 1oioo phenomenon equivalent to 

.. "lingual impedimaut." When the me.chine find.a the ~d.iment oeyond the 

tbrethold or critical value ot p:ronounceabil1t1 ,.._ in other words, When ~t it 

I 

\_ 

" 

trie• to enunciate \a "unpronounceable" in !ilgliah ..... it throws out the perm.utation ' 1, I 

selected and. be&ipa i;o repeat its aequence ot opere.ttona on the next ot the lOJ 

I 

permutations. / 

•I 

, , 

I 

.. ·- . ' - -"'"·--- ' . -... -f;-' . .. I "6-;1\. -= I I • • 
REF ID:A60419 

·- 1'he mcb1ne •houl.4 be able 111 thi• W¥ to •lim1nate a. ge&t JIBIQ" or 

the 101 per.mutations at a very rapid rate, :retaining onl1' a tev which au:rpua 

the critical. threahold or tt-pronounceab1111.i1''•. t'heae remaining poaei'bilitiea 

vill have to be examined visually or 11111toned tot' by the operator. 

r. A.laWJd.Dg the correct permutation ot the 10: high frequency 

letter• ha.I been 1•olAted. tbe ~·t rill cerle.inl.1' be able to till 1n the 

re•dning letters 'W1 thout too Ill.Oh ditticult;y .. 

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- - ------- ______ ....._ _________________________ _ 
- ~ - -- -

SNDMA GDVVM PXF[OC /OBPD 

DCVQX RIGVF vxo~z tL£FM I - --- • ., - "' • -

-- - -

OFYL r Jf1V P( CS VL C DPVD I . . 

_+ - -

OLEfFG tLLGD flSHYF t1TXDt1 

* !f:O':V fC -SC L £ P _ ( YI fi5 t14 IQ ~ \ 4 l 

D (/t>/ -~-~- -;t.;-i._ J) 

it ~\2=·; ,VJ J;--ll --- -- - ~ - --- -- - ---- -----

-- ---- ..... - --- -

t (J--~.._.J} 1-e. !:> - - --- ---
REF ID:A60419 

SMDMAGDVVMPXRDCIOBPDDCVQXRIGVFVXDLZF 

LEFMOFYLFIMVPYESVLEDPVDIOLEFGFLLGDAS 

MYFMTXDMROVFCSCLEPCYIMSMAIQGD 

A B 0 D E F G H I J K L M N 0 P Q R S T U V W X Y Z 

3 1 ~ 11 ~ 9 5 • 6 • • 8 10 • 4 5 2 3 5 1 • 9 • 4 4 1 

LE 4 

GD 3 

SM 3 

DM 2 

DC 2 

LEF 2 

t: 2 

l 

rs 1 

SC 1 

{: 2 

l 

[: 1 

l 

EF 2 

FL 2 

FM 2 

IO 2 

IM 2 

r: 1 

1 

[: l 

2 

r: 2 

l 

{: l 

l 

MA 2 

VF 2 

XR 2 

XD 2 

£: 

t: 

{: 

1 

1 

l 

3 

l 

1 
l. 

2. 

3. 

REF ID:A60419 

A frequency count of letters and digraphs was made as 

well as a chart showing the letters preceding and following each of the 

cipher letters. From these a table of reversed digraphs was made. 

The low frequency letters were marked as consonants. The 

letters occurring only once or twice account for only ' of the 101 letters of the message. The letters occurring 3 times were therefore added. 

This brought the frequency to 11, which was still below the 20% threshold. 

However if letters occurring 4 times are included, the total frequency 

would be 2.3. There are tests which might enable us to decide which of the 

4-frequency letters to include and which to exclude, but this might be 

difficult to build into a machine. 

A table was made of the letters preceding and following 

each of the assumed consonants A, R, Q, z, B and T. All the letters except c, E and Y appeared. Since letters which never contact low-frequency 

consonants are vecy likel;y consonants themselves, these three were added 

to the assumed consonants. The contact table then appeared as follows : 

ARQZBT CEY 

MMMMM 

GG 

DDD DD 

s s s s 

I I I I I 

0 0 

x XI 

v v 

LLLLL LL 

FF FFFF 

pp p p 

y y 

c 

E 
4. 

s. 

REF ID:A60419 

M, D, s, I, L, F and P seem to be the best prospects tor vowels. The 

substitutes for A, E, I and O should be found in this group. 

The reversed digraphs were studied with a view to 

identifying vowels. Since most reversed digraphs will be of' the f'om. 

c-v or v-c, it should be possible to separate most of the letters which 

reverse into two classes, these being identified as consonant or vowel 

by reference to (3). However since word divisions are not shown these 

indications may be somewhat blurred because the first letter of' one word 

may reverse with the last letter of the previous word. As a start only 

digraphs which reversed more than once were considered. 

SM 3 

MS l 

Y F 2 

FY l 

D M 2 

MD l 

VF 2 

F V l 

FL 2 

L F l 

These can be separated into two classes in two ways, (a) M F - D S V Y L 

and (b) M V Y L - D S F. From ( 3), V and Y are not very good prospects 

for vowels; therefore D, S, V, Y and L in (a) probably represent the c~­

sonants. This would make M, I, F and P the only good prospects to represent A, E, I and o. However we have the following contacts among these 

four letters : M P l, I M 2, F M 2, F I le In (b), M, V, Y and L 

probably represent the consonants. This would leave A, E, I and 0 to be 

found among D, s, F, I and P. There are only the following contacts 

among these five letters : D I l, D P 1, F I l, P D l. Since one of 

these five letters would be eliminated, the number of these presumed 

v-v contacts would probably be reduced further. All in all (b} seems 

like the more probable set-up. 

An attempt was made to identify the assumed vowels, 

D, s, F and the assumed consonants, M, v, Y, L • n, the highest trequency lettel",which also appeared doubled seemed almost certain to be 
REF ID:A60419 

E. F and S were assumed to be the two next most frequent vowels, A and 

0 respectively. As for the consonants, M, V, Y, L; V and L which OOcur 

doubled seemed like good prospects ror T and S respectively. M, the 

highest frequency consonant is probably N, H or R. From the first f'our 

letters or the message, SM D M, M=N seemed by far the best choice. 

'!'he worksheet now appeared as in Fig. 1. 

Changes were made in the plain text letter assumptions 

in order to make the fragments of text recovered look more like English. 

ONEN ETTN . . 6 MD MA GD V V M did not seem very likely. If we interchange the 

l .ll>V dL VS LT "lds ONEN ESSN which 

va nes o.1. an ' ~ ' = yie S M D M A G D V V M 

seems to be an improvement, although there is probably something still 

wrong. 

ATT E ON G F L L G D A S M suggests that G is H, R or L. G = R does not 

look very good in ~ ~ ~ i i ~ ~ and G == H does not look verr good in 

ONEN HESSN • ALATTLE 

S M D M A G D V V M • But G = L m F G F L L G D suggests F = I. The 

worksheet then looked as in Fig. 2. 

'!'he solution was completed using these recoveries. 

• N E N • L E S S is obviously A N /E N D L E S S • 
;---r- ,-- i- I I : 1- -JT~ ... --: f1T i~_-,--1 -ttt- -, 

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