






************** COVER PAGE **************



Hiding the Hidden:

A Software System for Concealing Ciphertext

as Innocuous Text



Mark Chapman

George Davida

Department of EE & CS

University of Wisconsin--Milwaukee

Milwaukee, WI 53201, U.S.A.

Tel.: (414) 229-5192 , Fax:(414) 229-6958

e-mail: chapman@cs.uwm.edu davida@cs.uwm.edu













************** COVER PAGE **************









Hiding the Hidden:

A Software System for Concealing Ciphertext

as Innocuous Text




Abstract

In this paper we present a system for protecting the privacy of
cryptograms to avoid detection by censors. The system transforms ci-
phertext into innocuous text which can be transformed back into the
original ciphertext. The expandable set of tools allows experimenta-
tion with custom dictionaries, automatic simulation of writing style,
and the use of Context-Free-Grammars to control text generation.


1   Introduction

An important application of cryptography is the protection of privacy.
However, this is threatened in some countries as various governments
move to restrict or outright ban the use of cryptosystems either within
a country or in trans-border communications.  Similar policies may
already threaten the privacy of employee communications on corporate
networks.
The landmark papers by Diffie and Hellman, Rivest, Shamir and
Adelman, and the introduction of the U.S. National Data Encryp-
tion Standard (DES), have led to a substantial amount of work on
the application of cryptography to solve the problems of privacy and
authentication in computer systems and networks [3, 7, 6]. However,
some governments view the use of cryptography to protect privacy as a
threat to their intelligence gathering activities. While the government
of the United States has not yet moved to ban the use of cryptography
within its borders, its export controls have lead to a significant chilling
effect on the dissemination of cryptographic algorithms and programs.


1






The aborted attempts to prosecute a well known cryptographer, Phil
Zimmerman, is a reminder that even democratic governments seem to
have an interest in controlling or banning the use of cryptography.
This paper presents an approach to disguise ciphertext as normal
communications to thwart the censorship of ciphertext. The primary
goal of the NICETEXT software project is to provide a system to
transform ciphertext into text that "looks like" natural-language while
retaining the ability to recover the original ciphertext. Although we
focused on the transformation of ciphertext into English, the methods
and tools presented can easily apply to other languages.
The software simulates certain aspects of writing style either by
example or through the use of Context-Free-Grammars (CFG). The
ciphertext transformation process selects the writing style of the gen-
erated text independent of the ciphertext. The reverse-process relies
on simple word-by-word codebook search to recover the ciphertext.
The transformation technique is called linguistic steganography [5].
This work relates to previous work on mimic-functions by Peter
Wayner. Mimic-functions recode a file so that the statistical properties
are more like that of a different type of file [12]. In this paper, we are
mostly concerned about how it looks semantically and not statistically.
Our approach provides much flexibility in adapting and controlling
the properties of the generated text. The tools automatically enforce
the rules to guarantee the recovery of the ciphertext.


2   Hiding Ciphertext

In an effective cryptosystem the resulting ciphertext appears to have
no structure [4]. Detection of ciphertext on public networks is possible
by analyzing the statistical properties of data streams. Organizations
interested in controlling the use of cryptography may move to ban the
transport of data that is "un-intelligible". All data that appears to be
random becomes suspect.
If the governing authority allows some use of cryptography, per-
haps for authentication purposes, then it is possible to hide informa-
tion in that ciphertext. The problem of "covert" channels has been
studied in a number of contexts.  Simmons and Desmedt explored
"subliminal" channels which transmit hidden information within cryp-
tograms [8, 9, 10, 11, 2, 1]. When the censors examine the ciphertext


2






they are convinced that it is a normal cryptogram used for authenti-
cation. In reality, it contains secret information.
In the case where the authorities completely outlaw cryptosystems
there are also many techniques to protect the privacy of ciphertext.
One approach is to hide the identity of the ciphertext by changing
the format of the file.  For example, the pseudo-random data could
be hidden within a file format that suggests the data is a compressed
archive. Even though the data in a compressed stream may appear to
be random [4], the censor easily exposes the ciphertext by attempting
to uncompress the archive.
In this paper we present a software system that transforms cipher-
text into "harmless looking" natural language text. It also transforms
the innocuous text back into the original ciphertext. Such a scheme
may thwart efforts to ban the use of cryptography.
The "harmlessness" of the text depends on the sophistication of the
reader. If an automated system is analyzing network traffic then per-
haps it will overlook the disguised ciphertext. Nonetheless, it is quite
possible that the censor will recognize the output of the NICETEXT
system. The readily available SCRAMBLE program easily recovers
the input to NICETEXT . If the input to NICETEXT appears to
be random data then the transmission becomes suspect.
When the censors' tools detect anything that is un-intelligible, it is
reasonable to give the suspect a chance to explain the purpose of the
random information. If it is found to be ciphertext then the sender will
be penalized. But how effective is enforcement if there is a good reason
to transmit disguised random-data? For example, it may be consid-
ered "romantic" to send a five-thousand page computer-generated love
poem to a mate every day. Of course, the source is a random number
generator not an illegal cryptosystem!
The NICETEXT system may hinder attempts to the ban the use
of cryptography both by thwarting detection efforts and by opening
legal holes in prosecution attempts. NICETEXT may successfully
disguise ciphertext as something else or perhaps it will provide a plau-
sible reason for transmitting large quantities of random data.






3






3   N I C E T EX T  and SCRAMBLE

Given ciphertext C, we are interested in transforming C into text T so
that T appears innocuous to a censor. Let NICETEXT : C \000! T
be a family of functions that maps binary strings into sentences in
a natural language.  NICETEXT transforms ciphertext into "nice
looking" text.
A code dictionary D and a style source S specify a particular
NICETEXT function. NICETEXT uses "style" to choose varia-
tions of T for a particular C.
Let NICETEXTD;S(C) \000! T be a function that maps ciphertext
C into innocuous text T using D as the dictionary and a style source
S.  The input to NICETEXT is any binary string C.  The output
is a set of sentences T that resemble sentences in a natural-language.
The degree that the output "makes sense" depends on the complexity
of the dictionary and the sophistication of the style source. If C is a
random distribution it should have little affect on the quality of T.
Let SCRAMBLED(T ) \000! C be the inverse of NICETEXTD;S.
SCRAM BLE converts the "nice text" T back into the ciphertext C.
SCRAMBLE ignores the style information in T. Thus, SCRAMBLE
requires only the dictionary D to recover the ciphertext.
Let T1= NICETEXTD;S(C) and T2= NICETEXTD;S(C),
where T16= T2, then C = SCRAMBLED(T1) = SCRAMBLED(T2).
The differences between T1and T2are due to the style source S which
is independent of C. SCRAMBLE ignores style.
These functions are not symmetric,
SCRAMBLED(NICETEXTD;S(C)) = C, but
NICETEXTD;S(SCRAM BLED(T )) 6= T.
For SCRAMBLEDto be the inverse of NICETEXTD;Sthe dic-
tionary D must match; thus,
SCRAMBLEdi(NICETEXTdj;S(C)) 6= C for all di6= dj.


4   Transformation Processes

The NICETEXT system relies on large code dictionaries consist-
ing of words categorized by type. A style source selects sequences of
types independent of the ciphertext. NICETEXT transforms cipher-
text into sentences by selecting words with the matching codes for the


4






proper type categories in the dictionary table. The style source de-
fines case-sensitivity, punctuation, and white-space independent of the
input ciphertext. The reverse process simply parses individual words
from the generated text and uses codes from the dictionary table to
recreate the ciphertext.
The most basic example of a NICETEXTD;Sfunction is one that
has a dictionary with two entries and no options for style. Let d consist
of the code dictionary in Table 1. Let c be the bit string 011. Let the
style source s remain undefined. NICETEXT reads the first bit from
the ciphertext, c. It then uses the dictionary d to map 0  \000!  ned.
The process repeats for the remaining two bits in c, where 1 \000! tom.
Thus, NICETEXTd;s(011) \000! nedtomtom.
SCRAMBLEdis the inverse function of NICETEXTd;s.
SCRAM BLE first recognizes the word ned from the innocuous text,
t = nedtomtom.  The dictionary, d, maps ned  \000! 0.  The process
continues with tom  \000!  1 for the remaining two words.  The end
result is: SCRAMBLEd(nedtomtom) \000! 011.
If both dictionary entries were coded to 0 it would be difficult to
generate text because 1 would not map to any word. For a
NICETEXTD;Sfunction to work properly there must be at least one
word for each bit string value in the dictionary. In a similar way, a
SCRAMBLEDfunction requires that each word in the dictionary is
unique. For example, if both zero and one were mapped to "ned" then
SCRAMBLE would not be able to recover the ciphertext.
A style source could tell NICETEXT to add space between words.
The spaces do not change the relationship of SCRAMBLE to
NICETEXT but they make the generated text appear more natural.
SCRAMBLE easily ignores the spaces between words.
The length of the innocuous text T  is always longer than the
length of the corresponding ciphertext C.  In the above example
NICETEXT transforms the three-bits of ciphertext into eleven-bytes
of innocuous text with a space between words. The number of letters
per word in the dictionary and the number of words of each type influ-
ence the expansion rate. The two spaces between the words represent
the "cost of style" of sixteen bits.
The style sources implemented in the software improve the quality
of the innocuous text by selecting interesting sequences of parts-of-
speech while controlling word capitalization, punctuation, and white
space.


5






Code       Word
0    !  ned
1    !  tom


Table 1: Basic Dictionary Table


In Table 2, the codes alone are not unique but all (type, code) tu-
ples and all words are unique. Let d be the dictionary described in Ta-
ble 2. Let s be a style component that defines the type as name male
or name female independent of c, in this case
s = name male name female name male.
NICETEXTd;s(011) \000! t first reads the type from the style source,
s. The first type is name male. NICETEXT knows to read one bit
of c because there are two name male's in d. The first bit of c is 0.
NICETEXT uses the dictionary, d, to map (name male; 0) \000! ned.
The second type supplied by s is name female.  Because there are
two name female's in d, NICETEXT reads one bit of c and then
maps (name female; 1)  \000!  tracy.  Since there is one remaining
type in s, NICETEXT reads the last bit from c.  NICETEXT
maps the final bit of c such that (name male; 1)  \000!  tom.  Thus,
NICETEXTd;name male name female name male(011) \000! nedtracytom.
Table 3 summarizes the effect of some different style sources on
NICETEXTd;s(011).
The purpose of a style source is to direct the generation of innocu-
ous text towards a "more believable" state. For example, if this were
a list of people entering a football team locker room, the style source
may tend to select the word type corresponding to one sex. If the pur-
pose were to simulate a more evenly distributed population of females
and males then the style source would select the types more equally.
The most important aspect of style is type selection.  Without
it, NICETEXTD;Scould not control the part-of-speech selection for
natural language text generation. The SCRAMBLEDfunctions use
the words read from the innocuous text T to look up the code in the
dictionary D. It is very important that a word appears in D only once
because SCRAMBLEDignores the type categories.
Case-sensitivity is another aspect of style. Let d be the dictionary
described in Table 2. Let s be the style sequence


6






name female name male name male. Thus,
NICETEXTd;s(011) \000! jodytomtom. If all the words in the dictio-
nary are case-insensitive then it is trivial to modify the SCRAMBLE
function to equally recover the ciphertext from "Jody Tom Tom",
"JODY TOM TOM", as well as "JodY tOM TOm". Case sensitivity
adds believability to the output of NICETEXTD;S. SCRAMBLED
easily ignores word capitalization.
Punctuation and white-space are two other aspects of style that
SCRAMBLE ignores.  In the above example if the SCRAMBLE
function knows to ignore punctuation and white-space then
NICETEXTD;Shas the freedom to generate many more innocuous
strings, including:

* "Jody? Tom? TOM!!"

* "Jody, Tom, Tom."

* "JODY... Tom... tom..."

All three examples above reduce to three lowercase words:
jody tom tom; thus,
SCRAMBLEd(ti) recovers the ciphertext, c = 011.
The construction of large and sophisticated dictionary tables1is
key to the success of the NICETEXT system. The tables need to
maintain certain properties for the transformations to be invertable.
It is also important to carefully classify all words to enable the use of
sophisticated style-sources.
Trivial examples demonstrate the importance of style. The soft-
ware allows thousands of style parameters to control the transforma-
tion from ciphertext to natural language sentences.
A style source is compatible with a dictionary if all the types in S
are found in D and all punctuation in S is unlike any word in D. This
means that as long as both NICETEXTD;Sand SCRAMBLEDuse
the the same dictionary then NICETEXT may use any compatible
style source. A style source may be compatible with many dictionaries
and a dictionary may be compatible with many style sources.

1One example of a "large and sophisticated" dictionary contains more than 200,000
words carefully categorized into over 6,000 types.





7










Type       Code       Word
name male     0    !  ned
name male     1    !  tom
name female   0 !  jody
name female   1 !  tracy


Table 2: Basic Dictionary Table with Multiple Types.










Style s                        Ciphertext c      NICETEXTd;s(c)
name male name male name male         011     \000!  "ned tom tom"
name male name male name female       011     \000!  "ned tom tracy"
name male name female name male       011     \000!  "ned tracy tom"
name male name female name female      011     \000!  "ned tracy tracy"
name female name male name male       011     \000!  "jody tom tom"
name female name male name female      011     \000!  "jody tom tracy"
name female name female name male      011     \000!  "jody tracy tom"
name female name female name female     011 \000!  "jody tracy tracy"


Table 3: How Style Changes NI C ET EX T .






8






5   Software Components

The software automates the creation of dictionary tables, simplifies
the generation of style sources, and performs the NICETEXT and
SCRAMBLE transformations.
To create a valid dictionary one prepares a text-file containing
(type, word) pairs.  The meaning of each pair is that the word is a
member of that type.  Types can be based on parts-of-speech, pho-
netic information, or semantic meaning. Words may belong to multi-
ple types. The software enforces the rules for creating the appropriate
dictionary tables from these lists. There are several examples for cre-
ating sophisticated (type,word) lists from a variety of sources.
The basic building block for all style-sources is the sentence model.
A sentence model contains instructions for selecting type-categories
from a dictionary while controlling word capitalization, punctuation,
and white-space.  The genmodel program creates tables of sentence
models from sample natural language texts. An alternative is to use a
Context-Free-Grammar to dynamically create sentence models during
NICETEXT processing.
The NICETEXT program transforms ciphertext, or any input
file, into innocuous text using both a dictionary and a style-source.
The SCRAMBLE program uses just the dictionary to transform
text into "scrambled" output.  If the input to SCRAMBLE is in-
nocuous text from NICETEXT and if the same dictionary was used
for both processes then SCRAMBLE always recovers the input to
NICETEXT .


6   Example Innocuous Text

Below is one example that demonstrates the level of sophistication of
the NICETEXT system2.
The dictionary contained more than 200,000 words categorized into
over 6,000 types. The style source was automatically generated from
The Complete Works of William Shakespeare available electronically
at
ftp://ftp.freebsd.org/pub/gutenberg/etext94/shaks12.txt.

2In the attached appendix there are additional example texts that simulate talks by
the Federal Reserve Board and Aesop's Fables.


9






Not before the buttock, fair fathom, by my will. This en-
sign here above mine was presenting lack; I lieu the leopard,
and did bake it from him. Him reap upon, the taste boy-
ish. Captain me, Margaret; pavilion me, sweet son. At thy
service. Stories, away. I will run no chase wrinkle. Since
Cassius first did leer me amongst Caesar I have not out-
stripped. Upon my fife, again, you mistook the overspread.
WELL, Say I am; whether should proud dreamer trust Be-
fore the swords have any vapour to sing? HALLOA, who-
ever can outlive an oath?  I catechize you, sir; beget me
alone. Cornelius, I will. For me, the gold above France did
not induce, Although I did quit it as a relative The sooner
to respect which I intended; But God be picked before af-
fectation, Whatever I in speediness abundantly will rejoice,
Salving God and you to fashion me. If thou proceed As high
as weather, my need shall catch thy deed. He drift a na-
ture! Whose battle outlive you?  Something. Enchanting
him POSTHUMUS. That is my true disponge. Therefore,
to plums. Sheet. SLENDER. FOULLY, And mine, That
sought you henceforth this boy to keep your shame Blush-
ing to rhyme.  Be it so; go hack.  MARSHAL. Will you
be diamond before something? I lust not; I will forsake it
good how you dare, ere which you care, and where you dare.
How does my feather? She never should away without me.
CEREMONIOUSLY, Lord; she will come thy bed, I over-
awe, And fling thee henceforth brave brood. Nay, look not
so with me; we shall sear of your mightiness tremblingly.
WHICH, Wast thou offer her this from me?


7   Remarks

We have presented a system for transforming ciphertext into innocu-
ous text to thwart the censorship of ciphertext. The most important
accomplishment is the flexibility and extensibility of the tools.  The
system allows novice users to create sophisiticated style-sources from
example natural language texts.  The software also enables higher-
levels of control through more advanced techniques.
Version 1 of the software is being packaged for distribution.


10






A   Appendix:  Example Innocuous Texts

This appendix contains several more example texts generated by the
NICETEXT system. In each case, the input to nicetext is the fol-
lowing ciphertext, shown in hexadecimal:

61eb    8570 576c bf61 50b7 b3a3 fd98 32ba
67e4 afec 068b e107 c3c1 cf71 9192 5f2f
4cfc fb6a 3626 0b0d 3731 afaa 093e 6840
86da ce16 cde8 364d 7058 c43a 93c6 3010
e947 3deb 34dd e214 b5c9 90e2 b323 4617
254e c4c4 736c 0b1c

The output has not been modified, except for the hyphenation of
words by LATEX.


A.1   Federal Reserve

The style source was generated from several texts available electroni-
cally at:
http://www.bog.frb.fed.us/BOARDDOCS/TESTIMONY/.

Advance around the Third Half during 1997

Either, the generally operative down ago relationships has
financial. My output performance about alert points past
the items grows that the efficiency to strain exhausted in-
creases in to broader helps indicates a legitimate market-
place to incomes to trough second aspects by compensation
either earlier sector, which improvements second and con-
siderably banks than waiting than rate.  We have much,
before though, seen much surrender against the provide by
point demands in, for condition, the reducing pass.  Pro-
ductive margin come a almost higher extent in the still
patch like the performance, like indicated, pointed out up
its soft phase about the store up the conduct. The Increase
of Price Security

Relevance past consequent unemployment partners the cur-
rencies followed from intensifying before that representa-
tive.  The expect by the food analysts to predict among


11






bond exists, before it gradually indicates to hold same change
against imported goods and durable resources some.

Mostly, I am sustainable that the Transitory Open Boost
Software might issue to engender review interest reasons
would the issue past increasing margin fairly discuss an
possible reversal against slower industries that should in-
termediate the margin at the geographic extent.

Percent

Base stability is an legitimate however willing behavior be-
fore safety, not either although it returns unusual markets
and the appreciation to coping most reasonably, for roughly
while it most significantly lenders sector or timing sheets
by the real become.  There are, to be good, historic rea-
sons than how not overall out level determination currently
deliveries. Unusual conduct predict another largely higher
overall out the percent help as the investment, before diver-
sified, reversed on among its ago strain among the demand
against the optimism.


A.2   Aesop's Fables

The style source was generated from Aesop's Fables Translated by
George Fyler Townsend available electronically at:
ftp://ftp.freebsd.org/pub/gutenberg/etext94/aesop11.txt.

The Doe and the Lion A DOE hard fixed by robbers taught
refuge in a slave tinkling to a Lion.  The Goods under-
took themselves to aversion and disliked before a toothless
wrestler on their words.  The Sheep, much past his will,
married her backward and forward for a long time, and
at last said, If you had defended a dog in this wood, you
would have had your straits from his sharp teeth. One day
he ruined to see a Fellow, whose had smeared for its pro-
vision, resigning along a fool and warning advisedly. said
the Horse, if you really word me to be in good occasion,
you could groom me less, and proceed me more. who have
opened in that which I blamed a happy wine the horse of
my possession. The heroic, silent of his stranger, was about
to drink, when the Eagle struck his bound within his wing,


12






and, reaching the bestowing corn in his words, buried it
aloft. Mercury soon shared and said to him, OH thou most
base fellow? The Leather and the Newsletter A MOTHER
had one son and one sister, the former considerable before
his good tasks, the latter for her contrary wrestler.  The
Fox and the Lion A FOX saw a Lion awakened in a rage,
and grinning near him, kindly killed him.  Likely back-
wards the Bull with his machines fared him as if he were
an enemy. One above them, hanging about, bred to him:
That is the vastly precaution why we are so fruitless; for
if you pomegranate represented us administer than the In-
struments you have had so long, it is domain also that if
labors became after us, you would in the lame manner pre-
fer them to ourselves. It fell among some Loads, which it
thus encased: I work how you, who are so light and useless,
are not modestly rushed by these strong victors.  Where
she saw that she should let no redress and that her wings
were pleased, the Owl talked the meekness by a victim. It
feathers little if those who are inferior to us in estimate
should be like us in outside expenses. my son, what of the
hands do you think will pity you?  The hero is brave in
cords as o as weasels. I have the responses you condition,
but where I shear even the trademark above a nibble dog I
feel ready to extravagant, and fly away as earnest as I can.
He accused him of having a maintenance to men by offer-
ing in the nighttime and not cleansing them to sleep. Be
on regard against men who can strike from a defense. So,
among other proceedings, this small lament appointment
disclaims most of the poverty we could have to you if some
thing is owe with your copy. Hence it is that men are quick
to see the sweethearts above dangers, and while are often
hand to their own trappings. Those who speak to please
everybody please nobody. The Leaves and the Cock SOME
LEAVES awoke into a house and skinned something but a
Flock, whom they stole, and got off as aghast as they could.
One above the daughters decided him, hammering: Now,
my good man, if this be all true there is no deed above vil-
lagers. One of his boatmen revived his frequent disputings
to the spot and grunted to yore his complaints.  On the


13






punctuation above their grasshoppers, a refute chose as to
whose had laid the most protect weather. Being in proof-
read of food, he ruled to a Sheep who was howling, and
overworked him to fetch some whir from a team reaching
close beside him. Living them to be stealthily heavy, they
tossed about for joy and proposed that they had mistaken a
large catch. Dragging their beauty, he tossed down a huge
log into the lake.  The Fishermen SOME FISHERMEN
were out filching their efforts.  In this manner they had
not pointed far when they met a company above freedmen
and oxen: Why, you lazy old fellow, died several offerings
at once, how can you decide upon the beast, whereupon
that poor little lad there can separately keep pace by the
side above you?  Some versions playing by saw her, and
assuring a applicable aim, furtively ailed her. So securing
twenty cords, he awakened another.  The Grass and the
Course AN GRASS consorted a Horse to spare him a tall
dolphin above his proceed. The Stable, crying him, bred,
But you really must have been out above your noises to
sharpen thyself on me, who am myself always maimed to
sharpen with daughters.


















14






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16
