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Reliable Deniable Communication: Hiding Messages in Noise Reliable Deniable Communication: Hiding Messages in Noise

Reliable Deniable Communication: Hiding Messages in Noise - PowerPoint Presentation

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Reliable Deniable Communication: Hiding Messages in Noise - PPT Presentation

The Chinese University of Hong Kong The Institute of Network Coding Pak Hou Che Mayank Bakshi Sidharth Jaggi Alice Reliability Bob Willie the Warden Reliability Deniability ID: 260628

proof theorem amp sketch theorem proof sketch amp codewords den iability theorems reliability deniability status bsc ogarithm vectors willie

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Slide1

Reliable Deniable Communication: Hiding Messages in Noise

The Chinese University

of Hong Kong

The Institute of

Network Coding

Pak

Hou

Che

Mayank

Bakshi

Sidharth

JaggiSlide2

Alice

Reliability

BobSlide3

Willie

(the Warden)

Reliability

Deniability

Alice

BobSlide4

 

M

T

t

 

 

Alice’s Encoder

 

 Slide5

 

M

T

Message

Trans. Status

 

BSC(

p

b

)

 

 

 

Alice’s Encoder

Bob’s Decoder

 

 

 Slide6

 

M

T

Message

Trans. Status

 

BSC(

p

b

)

 

 

 

Alice’s Encoder

Bob’s Decoder

BSC(p

w

)

 

 

 

 

Willie’s (Best) Estimator

 

 

 Slide7

Hypothesis Testing

Willie’s Estimate

Alice’s

Transmission Status

 Slide8

Hypothesis Testing

Willie’s Estimate

Alice’s

Transmission Status

Want:

 Slide9

Hypothesis Testing

Willie’s Estimate

Alice’s

Transmission Status

Want:

Known:

for opt. estimator

 Slide10

Hypothesis Testing

Willie’s Estimate

Alice’s

Transmission Status

Want:

Known:

for opt. estimator

,

(

w.h.p.

)

 Slide11

Bash, Goeckel & Towsley

[1]

Shared secret

[1] B. A. Bash, D.

Goeckel

and D.

Towsley

,

“Square root law for communication with low probability

of detection

on

AWGN

channels,”

in Proceedings of the IEEE International Symposium on

Information Theory

(ISIT)

, 2012, pp. 448–452.

AWGN channels

Capacity

=

bits

 

bits

 Slide12

This work

No shared secret

BSC(p

b

)

BSC(p

w

)

p

b

< p

wSlide13

Intuition

 Slide14

Intuition

 Slide15

Main Theorems

Theorem 1Deniability  low weight

codewordsTheorem 2 Converse of reliability

Theorem 3Achievability (reliability & deniability)Theorem 4Trade-off between deniability & size of codebookSlide16

Theorem 1 (wt(c.w

.))(high deniability => low weight codewords)

 Slide17

Theorem 2 (Converse)

, if

if

 Slide18

Theorems 2 &

3(Converse

& achievability for reliable & deniable comm.)Slide19

Theorems 2 & 3

 

 

0

1/2

1/2

p

b

>p

wSlide20

Theorems 2 & 3

 

 

0

1/2

1/2

 Slide21

Theorems 2 & 3

 

 

0

1/2

1/2

p

w

=1/2Slide22

Theorems 2 & 3

 

 

0

1/2

1/2

(

BSC(p

b

))Slide23

Theorems 2 & 3

 

 

0

1/2

1/2

p

b

=0Slide24

Theorems 2 & 3

 

 

0

1/2

1/2

 Slide25

Theorems 2 & 3

 

 

0

1/2

1/2

p

w

>

p

bSlide26

Theorems

2

& 3

 

 

0

1/2

1/2

 

“Standard” IT inequalities

+

wt

(“most

codewords

”)<

(

Thm

1)

 Slide27

Theorems 2 &

3

 

 

0

1/2

1/2

Achievable region

 

Main

thm

:Slide28
Slide29

Theorem 3 – Reliability

Random codebook ( i.i.d.

) )

minimum

distance decoderFor

,

 Slide30

Theorem 3 – Reliability proof sketch

.

.

.

1000001000000000100100000010000000100

0001000000100000010000000010000000001

0010000100000001010010000000100010011

0000100000010000000000010000000010000

Random code

codewords

 

Weight

 Slide31

Theorem 3 – Reliability proof sketch

.

.

.

1000001000010000100100000010000000100

0001000000100000010000000010000000001

0010000100000001010010000000100010011

0000100000010000000000010000000010000

E(Intersection of 2

codewords

) = O(1)

“Most”

codewords

“well-isolated”

 

Weight

 Slide32

Theorem 3 – Reliability proof sketch

.

.

.

1000001000010000100100000010000000100

0001000000100000010000000010000000001

0010000100000001010010000000100010011

0000100000010000000000010000000010000

E(Intersection of 2

codewords

) = O(1)

“Most”

codewords

“well-isolated”

Weight

 Slide33

Theorem 3 – dmin

decoding

Pr(x decoded to

x’) <

 

+

 

x

x

’Slide34

 

0

n

l

ogarithm of

# binary vectors

 Slide35

 

0

n

 

 

 

l

og(#

vector

s

)

 

 

 

 Slide36

l

og(#

vectors)

 

 Slide37

l

og(#

codewords

)

 

 Slide38

 

0

n

 

 

 

l

og(#

vectors)

 

 

 

 Slide39

Recall: want to show

 

Theorem 3 –

Den

iability

proof sketchSlide40

Recall: want to show

 

 

 

Theorem 3 –

Den

iability

proof sketchSlide41

 

0

n

l

og(#

vectors)

 

 

 

 

 

Theorem 3 – Deniability proof sketchSlide42

 

0

n

l

ogarithm of

#

codewords

Theorem 3 –

Den

iability

proof sketchSlide43

 

 

!!!

 

Theorem 3 –

Den

iability

proof sketchSlide44

 

 

!!!

 

 

Theorem 3 –

Den

iability

proof sketchSlide45

 

 

Theorem 3 –

Den

iability

proof sketch

with high probability

 Slide46
Slide47

 

0

n

 

 

 

l

ogarithm of

#

vectors

Theorem 3 – Deniability proof sketchSlide48

 

0

n

 

 

 

l

ogarithm of

#

vectors

Theorem 3 – Deniability proof sketchSlide49

# codewords of “type”

 

 

Theorem 3 –

Den

iability

proof sketchSlide50

 

 

Theorem 3 –

Den

iability

proof sketch

 Slide51

 

 

Theorem 3 –

Den

iability

proof sketch

 Slide52

 

 

Theorem 3 –

Den

iability

proof sketch

 Slide53

 

 

Theorem 3 –

Den

iability

proof sketch

 Slide54

w.p

.

 

 

Theorem 3 –

Den

iability

proof sketch

 Slide55

w.p

.

close to

w.p.

,

w.h.p

.

 

 

Theorem 3 –

Den

iability

proof sketch

 Slide56

Theorem 4

 

0

n

l

ogarithm of

#

codewordsSlide57

 

0

n

l

ogarithm of

#

codewords

Too

few

codewords

=> Not deniable

Theorem 4Slide58

Summary

 

 

0

1/2

1/2

Thm

1 & 2 Converse

(Upper Bound)

Thm

3 Achievability

Thm

4 Lower BoundSlide59

SummarySlide60

Summary