[PPT] - Towards Linguistic Steganography: A Systematic Investigation of PowerPoint Presentation

SLIDE 1

A project completed as part of the requirements for the BSc (Hons) of Science of Computing entitled

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues

by Richard Bergmair

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.1/44

SLIDE 2

Motivation

Why Linguistic Steganography?

Cryptosystems can protect sensitive data from

unauthorized access, by using a representation that makes a cryptogram impossible to interpret but

they do not conceal the very fact, that a

cryptogram has been exchanged

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.2/44

SLIDE 3

Motivation

Why Linguistic Steganography?

this is not a problem, as long as cryptography is

perceived at a broad (legal?) basis as a legitimate way of protecting one’s privacy, but

it is a problem, if it seen as a tool useful primarily

to potential terrorists. In order to protect the individual’s freedom of opinion and expression, we will have to deal with “Wendy the warden” trying to detect and penalize unwanted com- munication.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.3/44

SLIDE 4

Motivation

Why Linguistic Steganography?

Stegosystems can protect sensitive data from

being detected, by using a representation that makes steganograms appear as covers (a holiday image, a newspaper article, ...)

The more covers an arbitrator needs to analyze,

trying to detect a steganogram, the more difficult it will get.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.4/44

SLIDE 5

Motivation

Why Linguistic Steganography?

The vast masses of data coded in natural

language make for a good haystack to hide a needle in. Steganalytic efforts concentrating on digital images exchanged over the web might still be tractable, but it will hardly be possible to arbitrate all communication that takes place in natural language.

Natural language messages can easily be

transmitted over almost any medium.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.5/44

SLIDE 6

Steganographic Security

Alice and Bob want to exchange messages m

chosen from a message-space M over an insecure channel. They assume that data submitted over this channel is intercepted by Eve.

Alice and Bob have a key-distribution facility, which

equips them with keys k, chosen from a key-space

K. They can safely assume this channel to be

secure, in the sense of trusting it, not to expose the keys to Eve.

Alice and Bob want to make the insecure channel

secure, by making the security of the messages depend on the security of the keys.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.6/44

SLIDE 7

Steganographic Security

In the cryptographic setting,

Alice encrypts the message m, by choosing a

cryptogram e in accordance with the key k:

E(m, k) = e.

Bob decrypts the cryptogram e, i.e. reconstructs

the message m from e using k: D(e, k) = m. This is possible because ∀m, k : D(E(m, k), k) = m.

Eve tries to break the cryptogram. This is

impossible because it involves solving a difficult problem.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.7/44

SLIDE 8

Steganographic Security

✁

✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁ ✁

? untrusted

breaking encryption decryption

Eve Alice Bob

trusted key−distribution facility

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.8/44

SLIDE 9

Steganographic Security

✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✂ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄ ✄

? untrusted

contains hidden information? y/n

breaking

Alice Bob

trusted key−distribution facility

cover stego−object stego−object message message

embedding extraction

Wendy

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.9/44

SLIDE 10

Steganographic Security

In the steganographic setting,

Alice embeds the message m into a cover c, by

choosing a steganogram e in accordance with the key k: E(c, m, k) = e.

Bob extracts the message from the steganogram

e using k: D(e, k) = m. This is possible because ∀m, k : D(E(m, k), k) = m.

Eve tries to detect the steganogram. This is

impossible because there is a cover c′ such that the difference between e and c′ is imperceptible by humans, and machines trying to detect it face a difficult problem in the cryptographic sense.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.10/44

SLIDE 11

Steganographic Security

A difficult problem in the cryptographic sense can, for example, be

factoring the product of two large primes. (numeric

crypto, complexity-theoretic analysis)

guessing a key chosen from a key-space which is

as large as the message-space. (information-theoretic analysis)

solving a problem where the AI-community agrees

that it can easily be solved by intelligent humans, but that it cannot be solved within any known formal model. (HIPs)

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.11/44

SLIDE 12

Steganographic Security

K E C M X

H(M|X)

Q R S

H(K|E) H(M|E) H(C|E)

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.12/44

SLIDE 13

Steganographic Security

1/6 1/6 1/6 1/6

1 1 1 1 1

1/6 1/6 1/6 1/6

1

1/24 1/24 1/24 1/24

1/2 1/2

2/6

1

1/6 1/6 1/6 1/24 1/24 1/24 1/24 2/6 1/6 1/6 1/6 1/6 1/6 1/6 1/6 1/6 2/6 1/6 1/6

1 1 1 1 1 2/10 3/10 5/10

3/60 5/60 2/60 1/6 2/6 1/6 1/6 3/60 5/60 2/60

X M E C

formalization compression encryption mimicry

P Q R S T

interpretation

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.13/44

SLIDE 14

Lexical Steganography

C = {

Midshire is a nice little city, Midshire is a fine little town, Midshire is a great little town, Midshire is a decent little town, Midshire is a wonderful little town }

M = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 }

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.14/44

SLIDE 15

Lexical Steganography

Midshire is a

              

wonderful decent fine great nice

              

little

city

town

.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.15/44

SLIDE 16

Lexical Steganography

Midshire is a

              

00

wonderful

01

decent

10

fine

11

great

??

nice

              

little

city

1

town

.

10|1 = 1012 = 510

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.16/44

SLIDE 17

Lexical Steganography

Midshire is a

              

wonderful

1 decent

2 fine

3 great

4 nice

              

little

city

1 town

.
2,

1 5, 2

= 2 ∗ 2 + 1 = 5.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.17/44

SLIDE 18

Lexical Steganography

wonderful decent fine great nice

1

1
1
1
Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.18/44

SLIDE 19

Lexical Steganography

Midshire is a

              

wonderful

.5

10

decent

.25

110

fine

.125

1110

great

.0625

1111

nice

.0625               

little

city

.5

1

town

.5

.

10|1 = 1012 = 510

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.19/44

SLIDE 20

Lexical Steganography

All approaches we have seen so far have one basic idea in common: transforming a sequence of symbols

s1, s2, s3, . . . , sn

into a sequence

T(s1) | T(s2) | T(s3) | . . . | T(sn),

which has a “dual” interpretation, one with regard to the cover-channel, one with regard to a secret message.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.20/44

SLIDE 21

Context-Free Mimicry

A more sophisticated linguistic model can be achieved, by assuming the symbols as grammatical productions

S ⇒ α1, α1 ⇒ α2, α2 ⇒ α3, . . . , αm−1 ⇒ e.

into a sequence

T(S ⇒ α1) | T(α1 ⇒ α2) | T(α2 ⇒ α3) | . . . | T(αm−1 ⇒ e)

which has a “dual” interpretation, one with regard to the cover-channel, one with regard to a secret message.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.21/44

SLIDE 22

Chapman’s system

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.

[...]

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.22/44

SLIDE 23

Wayner’s system

It’s time for another game between the Whappers and the Blogs in scenic downtown Blovonia . I’ve just got to say that the Blog fans have come to support their team and rant and rave . Play Ball ! Time for another inning . The Whappers will be leading off . Baseball and Apple Pie . The pitcher spits. Herbert Herbertson swings the bat to get ready and enters the batter’s box . Here’s the fastball . He tries to bunt, and Robby Rawhide grabs it and tosses it to first . Hey, one down, two to go. Here we go. Prince Albert von Carmicheal swings the baseball bat to stretch and enters the batter’s box . Okay. Here’s the pitch It’s a spitter . High and outside . Ball . No contact in Mudsville ! Nothing on that one . Nice hit into short left field for a dangerous double and the throw is into the umpire’s head ! [...]

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.23/44

SLIDE 24

Winstein’s system

“Risky E-Vote System to Expand” Wired News (01/26/04); Zetter, Kim [...] She promises that the workplace computers people use to vote on SERVE will be

fortified(1) with firewalls and other intrusion countermeasures, and adds that election

fficials will recommend that home users install antivirus software on their PCs and run

virus checks prior to election day. Rubin counters that antivirus software can only identify known viruses, and thus is ineffective against new e-voting malware;

moreover(1) , attacks could go undetected

because SERVE lacks

elector(0) verifiability.

Rubin and the

three(1) other researchers who furnished the report were part of a

10-member expert panel enlisted by the Federal Voting Assistance Program (FVAP) to assess SERVE. Paquette reports that of the six remaining FVAP panel members, five recommended that the SERVE trial proceed, and one made no comment. [...] {bastioned(0), fortified(1)}, {furthermore(0), moreover(1)}, {elector(0), voter(1)}, {iii(0), three(1)}

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.24/44

SLIDE 25

Evaluation

For a number of reasons, I believe that the basic ap- proach that is most promising for building a secure and robust natural language steganography system in the near future is the lexical replacement system, simi- lar in principle to Winstein’s.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.25/44

SLIDE 26

Evaluation

The state of the art in computational linguistics and artificial intelligence is a significant limiting factor!

Do ontological semantics scale?
Even if they did, we do not have a reliable

common-sense ontology, yet.

Context-free grammars alone do not adequately

characterize natural languages. (anbncn respectively)

Style-templates were never meant to fool

sophisticated linguistic models or humans.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.26/44

SLIDE 27

Evaluation

Lexical models do scale!
And we even have large-scale resources available,

that cover all of everyday written language. (WordNet, for instance)

Lexical models do not dig very deep into the

semantic realm, but usually this will not be a problem, if

we use an embedding-approach, instead of a

generation-approach. This rather conservative approach follows the policy: “Use human language-competence as much as possible, and rely on formal models only when necessary!”

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.27/44

SLIDE 28

Evaluation

current systems

do not mimic cover-statistics adequately: They do

not mimic word-choice probabilities. A system similar in principle to Winstein’s, however following Wayner’s coding strategy, should be used instead.

do not encrypt messages adequately: Everyone

can extract the messages from the steganograms if he has the correct dictionary, respectively

grammar. (Shouldn’t linguistic knowledge be

assumed public wisdom? Language is, by definition, something public!) Messages should be encrypted with respect to key-distribution systems instead!

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.28/44

SLIDE 29

Evaluation

current systems

lack robustness. Some kind of error-correction

should be applied.

employ linguistically inadequate models: They use

disjunct interchangeability sets. Statistical word-sense disambiguation systems should be used instead.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.29/44

SLIDE 30

Lexical Ambiguity and Coding

move movement motion test work go run impress strike

(a) disjunct synsets

move test work go run impress strike movement motion

(b) natural synsets

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.30/44

SLIDE 31

Lexical Ambiguity and Coding

move test work go run impress strike movement motion

(c) “Forward ambiguity”

move test work go run impress strike movement motion

(d) “Backward ambiguity”

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.31/44

SLIDE 32

Lexical Ambiguity and Coding

... go ... ... run ... ... work ... ... move ...

(e) lexical semantics

Austria’s

ne of my

color national colors favourite copying− paper is blood is ... ... is colored ... ... is

(f) “contextual” semantics

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.32/44

SLIDE 33

Lexical Ambiguity and Coding

Uncle Joe turned out to be a brilliant player of the electric guitar.

C(brilliant) = Joe, turned, brilliant, player, electric, C(w) = w−3, w−2, w−1, w0, w1, w2, w3, P(C(x)|s) =

n

j=−n

P(wn|s), P(s|C(w)) = P(s)P(C(w)|s) P(C(w)) .

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.33/44

SLIDE 34

Lexical Ambiguity and Coding

rep(o) = dis(L(o), C(o)).

r ∈ rep(o) ⇒ r ∈

repA(o),

if rep(o) = rep(r)

repB(o), otherwise.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.34/44

SLIDE 35

Lexical Ambiguity and Coding

type-A-words o where repB(o) = ∅. Here we can be

sure that a replacement of word o will always be reversible automatically.

type-B-words o where repA(o) = ∅. Here we can be

sure that a replacement of word o will never be reversible automatically.

type-C-words o where repA(o) = ∅ ∧ repB(o) = ∅.

Here the question whether a replacement will be reversible depends on the actual replacement which is made.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.35/44

SLIDE 36

Secure and Robust Coding

[2] k l [2] k l [2] k l [2] k l b a [2] x y [2] p q r [3] n m

p

q r [6] n m

p

q r [6] p q r [3] x y [2] b a [2] b a [2] x y [2] x y [2] b a [2] p q r [3] p q r [3] n m

p

q r [6] n m

p

q r [6]

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.36/44

SLIDE 37

Secure and Robust Coding

[2] k l [12] [12] [12] [12] [2] k l [2] k l [2] k l b a [2] x y [2] p q r [3] n m

p

q r [6] n m

p

q r [6] p q r [3] x y [2] b a [2] b a [2] x y [2] p q r [3] n m

p

q r [6] n m

p

q r [6] b a [2] x y [2] p q r [3]

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.37/44

SLIDE 38

Secure and Robust Coding

[2] 1 [2] 1 [2] 1 [2] 1 [3] 1 2 [2] 1 [2] 1 [2] 1 [2] 1 [2] 1 [2] 1 [2] 1 [3] 1 2 [2] 1 [2] 1 [2] 1 [2] 1 [2] 1

[4] [6] [8] [8] [6] [4] [4] [4] "physical" elements "virtual" atomar elements to base coding on "split" prime factors [4] a b c d [4] p q r s [6] n

p

q r m [8] s t u v w x y z [8] s t u v w x y z [6] n

p

q r m [4] p q r s [4] a b c d

1 2 3 1 2 3 1 2 3 4 5 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 1 2 3 1 2 3

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.38/44

SLIDE 39

Secure and Robust Coding

[2] l [2] l [2] k l [2] k l k k

1 1 1 1

to be used with Method I b a [2] x y [2] p q r [3] n

p

q r [6] n m

p

q r [6] p q r [3] x y [2] b a [2] b a [2] n m

p

q r [6] n m

p

q r [6] p q r [3] b a [2] x y [2] p q r [3] x y [2] to be used with Method II m pseudorandom numbers seed

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.39/44

SLIDE 40

Secure and Robust Coding

= = = = = = = =

= = v

2

22

v

2

21

v

2

20

v

2

19

v

2

17

v

16

3

v

2

10

v

2

8

v

6

3

v

2

5

v

2

1

v

2

v

2

v

2

3

v

2

4

v

2

7

v

2

9

v

11

3

v

2

13 v

2

14 v

2

15 v 18

5

v

2

v

2

1 v

2

5

v

6

3

v

6

3

v

6

3

v

2

8

v

2

20 v

2

21 v

2

22 v 6

3

v

12

3

v

12

3

v

16

3

v

2

v

2

3

v

2

4

v

11

3

v

18

5

v

2

7

v

2

13 v

2

14 v

2

15

v

2

10

v

2

19

v

2

17

r s t u v w x y z

1 2 3 4 5 6 7 8

[9]

v( s ) s

5 5

z y x w v u t s [8]

1 2 3 4 5 6 7 v( s ) s

6 6

3 2 1 4 5

n

m

p q r [6]

v( s ) s

7 7

s

b c d

s 1 2 3

a

) v( 8

8

4

e [5]

v( s s

[4]

1 2 3 ) v(

p q r s

9

y x w v u t s [8]

1 2 3 4 5 6 v( s ) s

4 4

7

z

3 2 1 4 5

n

m

p q r [6]

v( s ) s

3 3

s

b c d

s

[4]

1 2 3

a

) v( 2

2

v( s s

[4]

1 2 3 ) v(

p q r s

1 1

s

b c d

s0

[4]

1 2 3

a

) v(

b c d [4]

1 2 3

a

v( 10 10 ) s s

v

2

9

[ 2

1

2 v ] )= s v(

[ 2 2

v v ] )= s v( 1

2 3

2 2 v v ] )= s v( 2

4 5

[ [

2 v v ] )= s v( 3

6 7

3

[ 2 2

v v v 2 ] v( s )=

4 8 9 10 [

v v ] )= s v(

[ 2 2

v v v 2 ] v( s )=

[

2 v v ] )= s v(

[ ]

)= s v(

[ 2 2

v v ] )= s v(

[ 2 2

v v ]

5 6 7 8 9

v( s10)=

11 12 13 14 15 16 17

3 3 3 v

18

5

19 20 21 22

0 0 1 1 1 0 0 1 0 1 0 1 0 1 1 1 0 0 1 0 0 0 0

v

]

4 5 6

16 15 15 2 2

3

3 2

[ [ [ ] ] ] [ ]

24

s’ s’ s’ s’ s’ s’

2

s’

1

secret secret 15

[

] [

360 secret

1. 2. 3. 4. 5. 6.

I II Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.40/44

SLIDE 41

Secure and Robust Coding

= = = = = = =

= =

=

r s t u v w x y z

1 2 3 4 5 6 7 8

[9]

v( s ) s

5 5

z y x w v u t s [8]

1 2 3 4 5 6 7 v( s ) s

6 6

3 2 1 4 5

n

m

p q r [6]

v( s ) s

7 7

s

b c d

s 1 2 3

a

) v( 8

8

4

e [5]

v( s s

[4]

1 2 3 ) v(

p q r s

9

y x w v u t s [8]

1 2 3 4 5 6 v( s ) s

4 4

7

z

3 2 1 4 5

n

m

p q r [6]

v( s ) s

3 3

s

b c d

s

[4]

1 2 3

a

) v( 2

2

v( s s

[4]

1 2 3 ) v(

p q r s

1 1

s

b c d

s0

[4]

1 2 3

a

) v(

b c d [4]

1 2 3

a

v( 10 10 ) s s

1. 2. 3. 4. 5. 6.

[ 2 2 ][ 2 2 ]

2 2 ]

[ [

2 ] 3

[ 2 2 2 ][ ][ 2 2 2 ][

2 ][

][ 2 2 ][ 2 2 ]

3 3 3 5

]

16 15 2 2 3 2

[ [ [ ] ] ] [ ]

24 15

[

] [

360 17

15

2 2 2 2 3 5 2 2 2 2

1 1 1 1 0 0

2 2 2 2 2 3 2 2 2 5 2 2 2 2 2 2 2 2 2 2 3 3 3

1 1 1 2 1 1 0 0 0 1 1 1 2 2 2

2 2 2 2 2 3 3 2 2 2 2 2 3

1 1 1

3

0 0 2 2 1 1 1 1 1 1 1 2

1 1 1 2 2 2 0 1 1 1 0 1 1 1 1 2= 3= 4= 2= 0= 5= 3= 3= 3=

16

0= 0=

255

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.41/44

SLIDE 42

Secure and Robust Coding

r s t u v w x y z

1 2 3 4 5 6 7 8

[9]

v( s ) s

5 5

z y x w v u t s [8]

1 2 3 4 5 6 7 v( s ) s

6 6

3 2 1 4 5

n

m

p q r [6]

v( s ) s

7 7

s

b c d

s 1 2 3

a

) v( 8

8

4

e [5]

v( s s

[4]

1 2 3 ) v(

p q r s

9

y x w v u t s [8]

1 2 3 4 5 6 v( s ) s

4 4

7

z

3 2 1 4 5

n

m

p q r [6]

v( s ) s

3 3

s

b c d

s

[4]

1 2 3

a

) v( 2

2

v( s s

[4]

1 2 3 ) v(

p q r s

1 1

s

b c d

s0

[4]

1 2 3

a

) v(

b c d [4]

1 2 3

a

v( 10 10 ) s s

1. 2. 3. 4. 5. 6.

[ 2 2 ][ 2 2 ]

2 2 ]

[ [

2 ] 3

[ 2 2 2 ][ ][ 2 2 2 ][

2 ][

][ 2 2 ][ 2 2 ]

3 3 3 5

]

16 15 2 2 3 2

[ [ [ ] ] ] [ ]

24 15

[

] [

360 255 17

2 2 2 2 3 5 2 2 2 2

1 1 0 0

2 2 2 2 2 3 2 2 2 5 2 2 2 2 2 2 2 2 2 2 3 3 3

1 1 1 2 1 1 0 0 0 1 1 1 2 2

2 2 2 2 2 3 3 2 2 2 2 2 3

1 1 1

3

0 0 2 2 1 1 1 1 1

1 1 1 2 2 0 1 1 1 0 1 1 2= 3= 4= 2= 0= 3= 3= 2= 1 0

1

2=

1 10 error error

16

0= 0=

error−correction error−correction Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.42/44

SLIDE 43

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues

A project conducted Oct-03 – Apr-04 by

Richard Bergmair

at University of Derby in Austria under supervision by

Stefan Katzenbeisser.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.43/44

SLIDE 44

This slide-set is not to be seen as a self-contained

document. Please conduct the project-report instead.

In particular, note that sources were not properly cited in this slide-set. See the citations given in the project-report for reference on sources.

Towards Linguistic Steganography: A Systematic Investigation of Approaches, Systems, and Issues – p.44/44