[PPT] - Natural Language Steganography and an AI-complete Security Primitive PowerPoint Presentation

SLIDE 1

Natural Language Steganography and an “AI-complete” Security Primitive

by Richard Bergmair

Oct-03 – Apr-04 University of Derby in Austria Technische Universität München conducted under the supervision of Stefan Katzenbeisser

Natural Language Steganography and an “AI-complete” Security Primitive – p.1/182

SLIDE 2

References

Natural Language Steganography and an “AI-complete” Security Primitive

for reference, see:

Richard Bergmair. Towards linguistic steganography: A

systematic investigation of approaches, systems, and

issues. April 2004. final year thesis. handed in in

partial fulfillment of the degree requirements for “B.Sc. (Hons.) of Computer Studies” to the University of

Derby. Available online: http://

bergmair.cjb.net/ pub/ towlingsteg-rep-inoff-a4.pdf

Natural Language Steganography and an “AI-complete” Security Primitive – p.2/182

SLIDE 3

References

Natural Language Steganography and an “AI-complete” Security Primitive

for reference, see:

Richard Bergmair and Stefan Katzenbeisser. Towards

human interactive proofs in the text-domain. In Kan Zhang and Yuliang Zheng, editors, Proceedings of the 7th Information Security Conference, volume 3225 of Lecture Notes in Computer Science, pages 257–267. Springer Verlag, September 2004. Available online: http:// bergmair.cjb.net/ pub/ towhiptext-proc.pdf

Natural Language Steganography and an “AI-complete” Security Primitive – p.3/182

SLIDE 4

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries.

Natural Language Steganography and an “AI-complete” Security Primitive – p.4/182

SLIDE 5

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries.

Wrong!

Natural Language Steganography and an “AI-complete” Security Primitive – p.5/182

SLIDE 6

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries.

Wrong! ...well, maybe not.

Natural Language Steganography and an “AI-complete” Security Primitive – p.6/182

SLIDE 7

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries.

Wrong! ...well, maybe not. ..., but then again...

Natural Language Steganography and an “AI-complete” Security Primitive – p.7/182

SLIDE 8

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries.

What is “evil”?

Natural Language Steganography and an “AI-complete” Security Primitive – p.8/182

SLIDE 9

Motivation

What is “evil”?

Natural Language Steganography and an “AI-complete” Security Primitive – p.9/182

SLIDE 10

Motivation

What is “evil”? “Hacker ethics” is about a good individual in a bad society.

Natural Language Steganography and an “AI-complete” Security Primitive – p.10/182

SLIDE 11

Motivation

What is “evil”? “Hacker ethics” is about a good individual in a bad society. “Witch hunt ethics” is about a bad individual in a good society.

Natural Language Steganography and an “AI-complete” Security Primitive – p.11/182

SLIDE 12

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries

Natural Language Steganography and an “AI-complete” Security Primitive – p.12/182

SLIDE 13

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries

like

the evil spy intercepting sensitive communication

Natural Language Steganography and an “AI-complete” Security Primitive – p.13/182

SLIDE 14

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries

like

the evil spy intercepting sensitive communication
the criminal fraudster replaying banking

transactions

Natural Language Steganography and an “AI-complete” Security Primitive – p.14/182

SLIDE 15

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries

like

the evil spy intercepting sensitive communication
the criminal fraudster replaying banking

transactions

the nosy neighbor reading your mail

Natural Language Steganography and an “AI-complete” Security Primitive – p.15/182

SLIDE 16

Motivation

Cryptosystems are designed to protect

ur sensitive data from evil adversaries

like

the evil spy intercepting sensitive communication
the criminal fraudster replaying banking

transactions

the nosy neighbor reading your mail

good individual / bad society?

Natural Language Steganography and an “AI-complete” Security Primitive – p.16/182

SLIDE 17

Motivation

Stegosystems are designed to hide our sensitive data from evil adversaries

Natural Language Steganography and an “AI-complete” Security Primitive – p.17/182

SLIDE 18

Motivation

Stegosystems are designed to hide our sensitive data from evil adversaries

like

the evil government censor infringing on our right

to freedom of opinion and expression.

Natural Language Steganography and an “AI-complete” Security Primitive – p.18/182

SLIDE 19

Motivation

Stegosystems are designed to hide our sensitive data from evil adversaries

like

the evil government censor infringing on our right

to freedom of opinion and expression.

the greedy employer limiting our access to

computers and anything which might teach us something about the way the world really works.

Natural Language Steganography and an “AI-complete” Security Primitive – p.19/182

SLIDE 20

Motivation

Stegosystems are designed to hide our sensitive data from evil adversaries

like

the evil government censor infringing on our right

to freedom of opinion and expression.

the greedy employer limiting our access to

computers and anything which might teach us something about the way the world really works.

good individual / bad society!

Natural Language Steganography and an “AI-complete” Security Primitive – p.20/182

SLIDE 21

Motivation

Evil spies,
criminal fraudsters, and
nosy neighbors

do not control your communication channel!

Natural Language Steganography and an “AI-complete” Security Primitive – p.21/182

SLIDE 22

Motivation

Evil spies,
criminal fraudsters, and
nosy neighbors

do not control your communication channel!

Evil governments and
greedy employers

do!

Natural Language Steganography and an “AI-complete” Security Primitive – p.22/182

SLIDE 23

Motivation

A shift in perspectives:

Natural Language Steganography and an “AI-complete” Security Primitive – p.23/182

SLIDE 24

Motivation

A shift in perspectives: Alice and Bob do not control their communication channel.

Natural Language Steganography and an “AI-complete” Security Primitive – p.24/182

SLIDE 25

Motivation

A shift in perspectives: Alice and Bob do not control their communication channel. Wendy the warden does!

Natural Language Steganography and an “AI-complete” Security Primitive – p.25/182

SLIDE 26

Motivation

What happens if Eve the eavesdropper intercepts a secure cryptogram?

Natural Language Steganography and an “AI-complete” Security Primitive – p.26/182

SLIDE 27

Motivation

What happens if Eve the eavesdropper intercepts a secure cryptogram? Nothing!

Natural Language Steganography and an “AI-complete” Security Primitive – p.27/182

SLIDE 28

Motivation

What happens if Eve the eavesdropper intercepts a secure cryptogram? Nothing!

the evil spy won’t know the sensitive information

Natural Language Steganography and an “AI-complete” Security Primitive – p.28/182

SLIDE 29

Motivation

What happens if Eve the eavesdropper intercepts a secure cryptogram? Nothing!

the evil spy won’t know the sensitive information
the criminal fraudster cannot read the banking

transaction

Natural Language Steganography and an “AI-complete” Security Primitive – p.29/182

SLIDE 30

Motivation

What happens if Eve the eavesdropper intercepts a secure cryptogram? Nothing!

the evil spy won’t know the sensitive information
the criminal fraudster cannot read the banking

transaction

the nosy neighbor won’t see the contents of your

mail

Natural Language Steganography and an “AI-complete” Security Primitive – p.30/182

SLIDE 31

Motivation

What happens if Wendy the warden intercepts a secure cryptogram?

Natural Language Steganography and an “AI-complete” Security Primitive – p.31/182

SLIDE 32

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

Natural Language Steganography and an “AI-complete” Security Primitive – p.32/182

SLIDE 33

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

What will witch-hunt ethics assert about the presupposedly bad individual in the good society, who seeks to conceal the content of his communication?

Natural Language Steganography and an “AI-complete” Security Primitive – p.33/182

SLIDE 34

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

What will witch-hunt ethics assert about the presupposedly bad individual in the good society, who seeks to conceal the content of his communication? That Alice and Bob have something evil to hide!

Natural Language Steganography and an “AI-complete” Security Primitive – p.34/182

SLIDE 35

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

the greedy employer will fire Alice and Bob

Natural Language Steganography and an “AI-complete” Security Primitive – p.35/182

SLIDE 36

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

the greedy employer will fire Alice and Bob
the evil government will send Alice and Bob to

Guantanomo Bay

Natural Language Steganography and an “AI-complete” Security Primitive – p.36/182

SLIDE 37

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

the greedy employer will fire Alice and Bob
the evil government will send Alice and Bob to

Auschwitz

Natural Language Steganography and an “AI-complete” Security Primitive – p.37/182

SLIDE 38

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

As long as there is a way for Wendy to tell ciphertext from cleartext, Alice and Bob will not live in peace!

Natural Language Steganography and an “AI-complete” Security Primitive – p.38/182

SLIDE 39

Motivation

What happens if Wendy the warden intercepts a secure cryptogram? Serious consequences!

As long as there is a way for Wendy to tell ciphertext from cleartext, Alice and Bob will not live in peace! Solution: Alice and Bob must use steganographic methods, rather than purely cryptographic ones, in

rder to hide not only the content of a message from

the adversary, but its very existence!

Natural Language Steganography and an “AI-complete” Security Primitive – p.39/182

SLIDE 40

Motivation

The difference between a cryptogram and a steganogram, is that a steganogram always appears innocuous to Wendy.

Natural Language Steganography and an “AI-complete” Security Primitive – p.40/182

SLIDE 41

Introduction

The difference between a cryptogram and a steganogram, is that a steganogram always appears innocuous to Wendy.

But what is innocuous?

Natural Language Steganography and an “AI-complete” Security Primitive – p.41/182

SLIDE 42

Introduction

The difference between a cryptogram and a steganogram, is that a steganogram always appears innocuous to Wendy.

But what is innocuous?

In the simplest case Wendy has a list of innocuous cover symbols.

Natural Language Steganography and an “AI-complete” Security Primitive – p.42/182

SLIDE 43

Introduction

C = { Midshires is a nice little city,

Midshires is a great little city, Midshires is a fine little city, Midshires is a decent little city, Midshires is a wonderful little city, Midshires is a nice little town, Midshires is a great little town}. If c ∈ C, then Wendy knows that c is innocuous.

Natural Language Steganography and an “AI-complete” Security Primitive – p.43/182

SLIDE 44

Introduction

M = { I don’t like my government!,

I don’t like my internet provider!, I don’t like my employer!, I’m wearing ladies’ underwear! }. Alice wants to send Bob a message m ∈ M.

Natural Language Steganography and an “AI-complete” Security Primitive – p.44/182

SLIDE 45

Introduction

Instead of enlisting C = {Midshires is a ...}:

We know an innocuous sentence

c = {Midshires is a nice little town, }

We have a dictionary, that tells us that the words

{nice, great, fine, decent, wonderful} and {city, town} are synonymous, i.e. mean the same.

We know that, by substituting a word in c by a

synonym, we never make an innocuous sentence suspicious, since we do not alter its meaning.

Natural Language Steganography and an “AI-complete” Security Primitive – p.45/182

SLIDE 46

Introduction

Instead of enlisting C = {Midshires is a ...}:

C = Midshires is a               

nice great fine decent wonderful

              

little

city

town

Natural Language Steganography and an “AI-complete” Security Primitive – p.46/182

SLIDE 47

Introduction

Instead of enlisting M = {I don’t like ...}:

We assume that Alice and Bob will exchange

arbitrary bitstrings, so M = {0, 1}∗

Natural Language Steganography and an “AI-complete” Security Primitive – p.47/182

SLIDE 48

Alice and Bob Fool Wendy

Midshires is a

              

00 nice 01 great 10 fine 11 decent ?? wonderful

              

little

0 city

1 town

.
m1 = 101 encodes to

c1 = Midshires is a fine little town

m2 = 010 encodes to

c2 = Midshires is a great little city

...

Natural Language Steganography and an “AI-complete” Security Primitive – p.48/182

SLIDE 49

Alice and Bob Fool Wendy

Midshires is a

              

00 nice 01 great 10 fine 11 decent ?? wonderful

              

little

0 city

1 town

.

Keith Winstein and Mark Chapman have actually built variants of this system.

Natural Language Steganography and an “AI-complete” Security Primitive – p.49/182

SLIDE 50

Wendy Strikes Back

Statistic characteristics of the secret message “show trough” to the word-choices in the steganogram!

Natural Language Steganography and an “AI-complete” Security Primitive – p.50/182

SLIDE 51

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m0 = 101
m1 = 001
m2 = 111
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.51/182

SLIDE 52

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m1 = 001
m2 = 111
m3 = 101
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.52/182

SLIDE 53

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m2 = 111
m3 = 101
m4 = 000
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.53/182

SLIDE 54

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m3 = 101
m4 = 000
m5 = 010
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.54/182

SLIDE 55

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m4 = 000
m5 = 010
m6 = 000
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.55/182

SLIDE 56

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m5 = 010
m6 = 000
m7 = 010
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.56/182

SLIDE 57

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m6 = 000
m7 = 010
m8 = 100
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.57/182

SLIDE 58

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m7 = 010
m8 = 100
m9 = 110
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.58/182

SLIDE 59

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m8 = 100
m9 = 110
m10 = 111
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.59/182

SLIDE 60

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m9 = 110
m10 = 111
m11 = 100
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.60/182

SLIDE 61

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m10 = 111
m11 = 100
m12 = 111
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.61/182

SLIDE 62

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m11 = 100
m12 = 111
m13 = 011
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.62/182

SLIDE 63

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m12 = 111
m13 = 011
m14 = 011
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.63/182

SLIDE 64

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m13 = 011
m14 = 011
m15 = 000
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.64/182

SLIDE 65

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m14 = 011
m15 = 000
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.65/182

SLIDE 66

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
m15 = 000
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.66/182

SLIDE 67

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.67/182

SLIDE 68

Wendy Strikes Back

Innocuous covers have statistic characteristics originating from the way native speakers use the language.

Natural Language Steganography and an “AI-complete” Security Primitive – p.68/182

SLIDE 69

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c0 = Midshires is a nice little town
c1 = Midshires is a nice little city
c2 = Midshires is a nice little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.69/182

SLIDE 70

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c1 = Midshires is a nice little city
c2 = Midshires is a nice little town
c3 = Midshires is a nice little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.70/182

SLIDE 71

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c2 = Midshires is a nice little town
c3 = Midshires is a nice little town
c4 = Midshires is a nice little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.71/182

SLIDE 72

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c3 = Midshires is a nice little town
c4 = Midshires is a nice little city
c5 = Midshires is a great little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.72/182

SLIDE 73

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c4 = Midshires is a nice little city
c5 = Midshires is a great little city
c6 = Midshires is a nice little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.73/182

SLIDE 74

Wendy Strikes Back

is a

              

00 nice

|||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c5 = Midshires is a great little city
c6 = Midshires is a nice little town
c7 = Midshires is a decent little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.74/182

SLIDE 75

Wendy Strikes Back

is a

              

00 nice

|||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c6 = Midshires is a nice little town
c7 = Midshires is a decent little town
c8 = Midshires is a great little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.75/182

SLIDE 76

Wendy Strikes Back

is a

              

00 nice

||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c7 = Midshires is a decent little town
c8 = Midshires is a great little town
c9 = Midshires is a nice little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.76/182

SLIDE 77

Wendy Strikes Back

is a

              

00 nice

||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c8 = Midshires is a great little town
c9 = Midshires is a nice little town
c10 = Midshires is a wonderful little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.77/182

SLIDE 78

Wendy Strikes Back

is a

              

00 nice

||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c9 = Midshires is a nice little town
c10 = Midshires is a wonderful little town
c11 = Midshires is a great little town
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.78/182

SLIDE 79

Wendy Strikes Back

is a

              

00 nice

|||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c10 = Midshires is a wonderful little town
c11 = Midshires is a great little town
c12 = Midshires is a great little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.79/182

SLIDE 80

Wendy Strikes Back

is a

              

00 nice

|||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.
c11 = Midshires is a great little town
c12 = Midshires is a great little city
c13 = Midshires is a fine little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.80/182

SLIDE 81

Wendy Strikes Back

is a

              

00 nice

|||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

|||||||||

.
c12 = Midshires is a great little city
c13 = Midshires is a fine little city
c14 = Midshires is a nice little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.81/182

SLIDE 82

Wendy Strikes Back

is a

              

00 nice

|||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

|||||||||

.
c13 = Midshires is a fine little city
c14 = Midshires is a nice little city
c15 = Midshires is a fine little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.82/182

SLIDE 83

Wendy Strikes Back

is a

              

00 nice

|||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

|||||||||

.
c14 = Midshires is a nice little city
c15 = Midshires is a fine little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.83/182

SLIDE 84

Wendy Strikes Back

is a

              

00 nice

||||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

|||||||||

.
c15 = Midshires is a fine little city
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.84/182

SLIDE 85

Wendy Strikes Back

is a

              

00 nice

||||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

|||||||||

.
...

Natural Language Steganography and an “AI-complete” Security Primitive – p.85/182

SLIDE 86

Wendy Strikes Back

is a

              

00 nice

||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

||||||||

.

is a

              

00 nice

||||||||

01 great

||||

10 fine

||||

11 decent

||||

?? wonderful

||||               

little

0 city

||||||||

1 town

|||||||||

.

Natural Language Steganography and an “AI-complete” Security Primitive – p.86/182

SLIDE 87

Alice, Bob, and Huffman

This weakness is due to

ur use of block codes!

Natural Language Steganography and an “AI-complete” Security Primitive – p.87/182

SLIDE 88

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.88/182

SLIDE 89

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.89/182

SLIDE 90

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.90/182

SLIDE 91

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.91/182

SLIDE 92

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.92/182

SLIDE 93

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.93/182

SLIDE 94

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.94/182

SLIDE 95

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.95/182

SLIDE 96

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.96/182

SLIDE 97

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.97/182

SLIDE 98

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.98/182

SLIDE 99

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.99/182

SLIDE 100

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.100/182

SLIDE 101

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.101/182

SLIDE 102

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.102/182

SLIDE 103

Alice, Bob, and Huffman

00101110110010111001011100010100 00

||||||||

01

||||||||

10

||||||||

11

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.103/182

SLIDE 104

Alice, Bob, and Huffman

00101110110010111001011100010100 00

|||||||| p = 1/4 (00, 01, 10, 11)

01

|||||||| p = 1/4 (00, 01, 10, 11)

10

|||||||| p = 1/4 (00, 01, 10, 11)

11

|||||||| p = 1/4 (00, 01, 10, 11)

Natural Language Steganography and an “AI-complete” Security Primitive – p.104/182

SLIDE 105

Alice, Bob, and Huffman

This weakness is due to

ur use of block codes!

However, we can overcome it, by using prefix-free variable length codes.

Natural Language Steganography and an “AI-complete” Security Primitive – p.105/182

SLIDE 106

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.106/182

SLIDE 107

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.107/182

SLIDE 108

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.108/182

SLIDE 109

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.109/182

SLIDE 110

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.110/182

SLIDE 111

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.111/182

SLIDE 112

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.112/182

SLIDE 113

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.113/182

SLIDE 114

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.114/182

SLIDE 115

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.115/182

SLIDE 116

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.116/182

SLIDE 117

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.117/182

SLIDE 118

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.118/182

SLIDE 119

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.119/182

SLIDE 120

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.120/182

SLIDE 121

Alice, Bob, and Huffman

001000110001001110111101011010

||||||||

10

||||||||

110

||||||||

1110

||||||||

1111

||||||||

Natural Language Steganography and an “AI-complete” Security Primitive – p.121/182

SLIDE 122

Alice, Bob, and Huffman

001000110001001110111101011010

|||||||| p = 1/2 (0, 1)

10

|||||||| p = 1/4 (00, 01, 10, 11)

110

|||||||| p = 1/8 (000, 001, ..., 110, ...)

1110

|||||||| p = 1/16 (0000, 0001, ..., 1110, ...)

1111

|||||||| p = 1/16 (0000, 0001, ..., 1111, ...)

Natural Language Steganography and an “AI-complete” Security Primitive – p.122/182

SLIDE 123

Alice, Bob, and Huffman

001000110001001110111101011010

|||||||| p = 1/2 (0, 1)

10

|||||||| p = 1/4 (00, 01, 10, 11)

110

|||||||| p = 1/8 (000, 001, ..., 110, ...)

1110

|||||||| p = 1/16 (0000, 0001, ..., 1110, ...)

1111

|||||||| p = 1/16 (0000, 0001, ..., 1111, ...)

The use of prefix free variable length codes in steganography is due to Peter Wayner!

Natural Language Steganography and an “AI-complete” Security Primitive – p.123/182

SLIDE 124

Wendy’s Cryptographic Problem

By word-choice encoding on the basis of a

Huffman-code we can provide mimicry.

Natural Language Steganography and an “AI-complete” Security Primitive – p.124/182

SLIDE 125

Wendy’s Cryptographic Problem

By word-choice encoding on the basis of a

Huffman-code we can provide mimicry.

Mimicry turns a secret message m ∈ M to an

innocuous looking cover c ∈ C.

Natural Language Steganography and an “AI-complete” Security Primitive – p.125/182

SLIDE 126

Wendy’s Cryptographic Problem

By word-choice encoding on the basis of a

Huffman-code we can provide mimicry.

Mimicry turns a secret message m ∈ M to an

innocuous looking cover c ∈ C.

To know whether our scheme is

steganographically secure, we have to ask

urselves the following question:

Natural Language Steganography and an “AI-complete” Security Primitive – p.126/182

SLIDE 127

Wendy’s Cryptographic Problem

By word-choice encoding on the basis of a

Huffman-code we can provide mimicry.

Mimicry turns a secret message m ∈ M to an

innocuous looking cover c ∈ C.

To know whether our scheme is

steganographically secure, we have to ask

urselves the following question:

If it is trivial for Bob to decode a message, then why shouldn’t Wendy do the very same thing?

Natural Language Steganography and an “AI-complete” Security Primitive – p.127/182

SLIDE 128

Wendy’s Cryptographic Problem

BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.128/182

SLIDE 129

Wendy’s Cryptographic Problem

steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.129/182

SLIDE 130

Wendy’s Cryptographic Problem

kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.130/182

SLIDE 131

Wendy’s Cryptographic Problem

Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.131/182

SLIDE 132

Wendy’s Cryptographic Problem

mimicry−1 Wendy can reverse this ????? Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.132/182

SLIDE 133

Wendy’s Cryptographic Problem

distinguish this. Wendy can mimicry−1 Wendy can reverse this ????? Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.133/182

SLIDE 134

Wendy’s Cryptographic Problem

BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.134/182

SLIDE 135

Wendy’s Cryptographic Problem

cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.135/182

SLIDE 136

Wendy’s Cryptographic Problem

steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.136/182

SLIDE 137

Wendy’s Cryptographic Problem

kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.137/182

SLIDE 138

Wendy’s Cryptographic Problem

Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.138/182

SLIDE 139

Wendy’s Cryptographic Problem

10101110110 01110111011 01010101011 01110110110 mimicry−1 Wendy can reverse this Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.139/182

SLIDE 140

Wendy’s Cryptographic Problem

distinguish this. Wendy cannot 10101110110 01110111011 01010101011 01110110110 mimicry−1 Wendy can reverse this Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.140/182

SLIDE 141

Wendy’s Cryptographic Problem

????? encryption −1 reverse this Wendy cannot without a key distinguish this. Wendy cannot 10101110110 01110111011 01010101011 01110110110 mimicry−1 Wendy can reverse this Wendy cannot distinguish this. kid writing home from summer camp

ut of here!

sucks! Get me Summer camp Dear Dad! steganogram the summer camp!

f fun, here at

We’re having a lot Dear Grandma! mimicry cryptogram 00101010110 01010110111 01011010011 01011101100 encryption BRIDGES OUT plaintext Alice

Natural Language Steganography and an “AI-complete” Security Primitive – p.141/182

SLIDE 142

Wendy’s Linguistic Problem

And now to something completely different!

Natural Language Steganography and an “AI-complete” Security Primitive – p.142/182

SLIDE 143

Wendy’s Linguistic Problem

And now to something completely different!

AI-complete /A-I k*m-pleet’/ [MIT, Stanford: by analogy with ‘NP-complete’ (see NP-)] adj. Used to describe problems or subproblems in AI, to indicate that the solution presupposes a solution to the ‘strong AI problem’ (that is, the synthesis of a human-level intelligence). A problem that is AI-complete is, in other words, just too hard[...] The Jargon Files

Natural Language Steganography and an “AI-complete” Security Primitive – p.143/182

SLIDE 144

Wendy’s Linguistic Problem

Humans can easily solve AI-complete problems.

Natural Language Steganography and an “AI-complete” Security Primitive – p.144/182

SLIDE 145

Wendy’s Linguistic Problem

Humans can easily solve AI-complete problems.
Computers cannot.

Natural Language Steganography and an “AI-complete” Security Primitive – p.145/182

SLIDE 146

Wendy’s Linguistic Problem

Humans can easily solve AI-complete problems.
Computers cannot.
Wendy is a computer.

Natural Language Steganography and an “AI-complete” Security Primitive – p.146/182

SLIDE 147

Wendy’s Linguistic Problem

Humans can easily solve AI-complete problems.
Computers cannot.
Wendy is a computer.
If reversing our steganographic embedding yields

an AI-complete problem, Wendy is truly in trouble.

Natural Language Steganography and an “AI-complete” Security Primitive – p.147/182

SLIDE 148

Wendy’s Linguistic Problem

Humans can easily solve AI-complete problems.
Computers cannot.
Wendy is a computer.
If reversing our steganographic embedding yields

an AI-complete problem, Wendy is truly in trouble.

We can construct such a system, by using the

linguistic problem of word-sense disambiguation.

Natural Language Steganography and an “AI-complete” Security Primitive – p.148/182

SLIDE 149

Wendy’s Linguistic Problem

It should move through several more drafts.
It should run through several more drafts.
It should go through several more drafts.

Natural Language Steganography and an “AI-complete” Security Primitive – p.149/182

SLIDE 150

Wendy’s Linguistic Problem

It should move through several more drafts.
It should run through several more drafts.
It should go through several more drafts.
All articles must move through copy-editing.
All articles must run through copy-editing.
All articles must go through copy-editing.

Natural Language Steganography and an “AI-complete” Security Primitive – p.150/182

SLIDE 151

Wendy’s Linguistic Problem

It should move through several more drafts.
It should run through several more drafts.
It should go through several more drafts.
All articles must move through copy-editing.
All articles must run through copy-editing.
All articles must go through copy-editing.

syn(move) = {move, run, go}

??

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SLIDE 152

Wendy’s Linguistic Problem

That sermon will move people.
That sermon will impress people.
That sermon will strike people.

Natural Language Steganography and an “AI-complete” Security Primitive – p.152/182

SLIDE 153

Wendy’s Linguistic Problem

That sermon will move people.
That sermon will impress people.
That sermon will strike people.
Your speech must move the audience.
Your speech must impress the audience.
Your speech must strike the audience.

Natural Language Steganography and an “AI-complete” Security Primitive – p.153/182

SLIDE 154

Wendy’s Linguistic Problem

That sermon will move people.
That sermon will impress people.
That sermon will strike people.
Your speech must move the audience.
Your speech must impress the audience.
Your speech must strike the audience.

syn(move) = {move, impress, strike}

??

Natural Language Steganography and an “AI-complete” Security Primitive – p.154/182

SLIDE 155

Wendy’s Linguistic Problem

Can we conclude that all these words are generally synonymous to move?

syn(move) = {move, run, go, impress, strike}

Natural Language Steganography and an “AI-complete” Security Primitive – p.155/182

SLIDE 156

Wendy’s Linguistic Problem

Can we conclude that all these words are generally synonymous to move?

syn(move) = {move, run, go, impress, strike}

Unfortunately, we can’t.

Natural Language Steganography and an “AI-complete” Security Primitive – p.156/182

SLIDE 157

Wendy’s Linguistic Problem

It should move through several more drafts.
It should run through several more drafts.
It should go through several more drafts.

Natural Language Steganography and an “AI-complete” Security Primitive – p.157/182

SLIDE 158

Wendy’s Linguistic Problem

It should move through several more drafts.
It should run through several more drafts.
It should go through several more drafts.

BUT

Your speech must move the audience.
*Your speech must run the audience.
*Your speech must go the audience.

Natural Language Steganography and an “AI-complete” Security Primitive – p.158/182

SLIDE 159

Wendy’s Linguistic Problem

That sermon will move people.
That sermon will impress people.
That sermon will strike people.

Natural Language Steganography and an “AI-complete” Security Primitive – p.159/182

SLIDE 160

Wendy’s Linguistic Problem

That sermon will move people.
That sermon will impress people.
That sermon will strike people.

BUT

All articles must move through copy-editing.
*All articles must impress through copy-editing.
*All articles must strike through copy-editing.

Natural Language Steganography and an “AI-complete” Security Primitive – p.160/182

SLIDE 161

Wendy’s Linguistic Problem

We cannot include a synset like

syn(move) = {move, run, go, impress, strike}

in a dictionary! All we can do is to state that

syn(c1, move)

= {move, run, go}

syn(c2, move)

= {move, impress, strike}

for some linguistic contexts c1 = c2.

Natural Language Steganography and an “AI-complete” Security Primitive – p.161/182

SLIDE 162

Wendy’s Linguistic Problem

Recall the way our encoder works:

We have an innocuous sentence:

That sermon will impress people

Natural Language Steganography and an “AI-complete” Security Primitive – p.162/182

SLIDE 163

Wendy’s Linguistic Problem

Recall the way our encoder works:

We have an innocuous sentence:

That sermon will impress people

We have a set of words that can be replaced for

this {move, impress, strike}

Natural Language Steganography and an “AI-complete” Security Primitive – p.163/182

SLIDE 164

Wendy’s Linguistic Problem

Recall the way our encoder works:

We have an innocuous sentence:

That sermon will impress people

We have a set of words that can be replaced for

this {move, impress, strike}

We assign codewords to them like

move → 0, impress → 10, strike → 11

Natural Language Steganography and an “AI-complete” Security Primitive – p.164/182

SLIDE 165

Wendy’s Linguistic Problem

Recall the way our encoder works:

We have an innocuous sentence:

That sermon will impress people

We have a set of words that can be replaced for

this {move, impress, strike}

We assign codewords to them like

move → 0, impress → 10, strike → 11

To send a secret 0, we transmit

That sermon will move people

Natural Language Steganography and an “AI-complete” Security Primitive – p.165/182

SLIDE 166

Wendy’s Linguistic Problem

How would Wendy steganalyze this?

She intercepts

That sermon will move people

Natural Language Steganography and an “AI-complete” Security Primitive – p.166/182

SLIDE 167

Wendy’s Linguistic Problem

How would Wendy steganalyze this?

She intercepts

That sermon will move people

Now she has to find the code for move.

Natural Language Steganography and an “AI-complete” Security Primitive – p.167/182

SLIDE 168

Wendy’s Linguistic Problem

How would Wendy steganalyze this?

She intercepts

That sermon will move people

Now she has to find the code for move.
However, there will be multiple codes for this:
move → 0, impress → 10, strike → 11 (correct)
run → 0, move → 10, go → 11 (incorrect)

Natural Language Steganography and an “AI-complete” Security Primitive – p.168/182

SLIDE 169

Wendy’s Linguistic Problem

How would Wendy steganalyze this?

She intercepts

That sermon will move people

Now she has to find the code for move.
However, there will be multiple codes for this:
move → 0, impress → 10, strike → 11 (correct)
run → 0, move → 10, go → 11 (incorrect)
In order to decode this replacement, Wendy has to

solve an instance of the AI-complete problem of word-sense ambiguity!

Natural Language Steganography and an “AI-complete” Security Primitive – p.169/182

SLIDE 170

Concluding Remarks

We showed that steganography can be motivated

by the application of hacker ethics to cryptographic system design.

Natural Language Steganography and an “AI-complete” Security Primitive – p.170/182

SLIDE 171

Concluding Remarks

We showed that steganography can be motivated

by the application of hacker ethics to cryptographic system design.

We showed a simple technique to hide data by

replacing words in innocuous text by synonyms.

Natural Language Steganography and an “AI-complete” Security Primitive – p.171/182

SLIDE 172

Concluding Remarks

We showed that steganography can be motivated

by the application of hacker ethics to cryptographic system design.

We showed a simple technique to hide data by

replacing words in innocuous text by synonyms.

We showed how to detect such steganograms

using statistic patterns.

Natural Language Steganography and an “AI-complete” Security Primitive – p.172/182

SLIDE 173

Concluding Remarks

We showed how to improve the technique, so that

detection becomes more difficult.

Natural Language Steganography and an “AI-complete” Security Primitive – p.173/182

SLIDE 174

Concluding Remarks

We showed how to improve the technique, so that

detection becomes more difficult.

We showed an approach towards making the

technique secure against arbitrators who do not have a certain key.

Natural Language Steganography and an “AI-complete” Security Primitive – p.174/182

SLIDE 175

Concluding Remarks

We showed how to improve the technique, so that

detection becomes more difficult.

We showed an approach towards making the

technique secure against arbitrators who do not have a certain key.

We showed an approach towards making the

technique secure against arbitrators who are not human.

Natural Language Steganography and an “AI-complete” Security Primitive – p.175/182

SLIDE 176

Concluding Remarks

We did not review the actual systems implemented

so far.

Natural Language Steganography and an “AI-complete” Security Primitive – p.176/182

SLIDE 177

Concluding Remarks

We did not review the actual systems implemented

so far.

We did not review much related literature.

Natural Language Steganography and an “AI-complete” Security Primitive – p.177/182

SLIDE 178

Concluding Remarks

We did not review the actual systems implemented

so far.

We did not review much related literature.
We did not show how to make the technique

robust.

Natural Language Steganography and an “AI-complete” Security Primitive – p.178/182

SLIDE 179

Concluding Remarks

We did not review the actual systems implemented

so far.

We did not review much related literature.
We did not show how to make the technique

robust.

We did not show how to use our linguistic

properties for simple human interactive proofs.

Natural Language Steganography and an “AI-complete” Security Primitive – p.179/182

SLIDE 180

Concluding Remarks

We did not review the actual systems implemented

so far.

We did not review much related literature.
We did not show how to make the technique

robust.

We did not show how to use our linguistic

properties for simple human interactive proofs. Please see the provided references for these things!

Natural Language Steganography and an “AI-complete” Security Primitive – p.180/182

SLIDE 181

This slide-set is not a self-contained publication. Please conduct the references 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.

Natural Language Steganography and an “AI-complete” Security Primitive – p.181/182

SLIDE 182

References

Natural Language Steganography and an “AI-complete” Security Primitive

for reference, see:

Richard Bergmair. Towards linguistic steganography: A

systematic investigation of approaches, systems, and

issues. April 2004.
Richard Bergmair and Stefan Katzenbeisser. Towards

human interactive proofs in the text-domain. September 2004. Available online: http://bergmair.cjb.net/

Natural Language Steganography and an “AI-complete” Security Primitive – p.182/182