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Paul Cuff Paul Cuff

Paul Cuff - PowerPoint Presentation

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Paul Cuff - PPT Presentation

The Source Coding Side of Secrecy TexPoint fonts used in EMF Read the TexPoint manual before you delete this box A A Game Theoretic Secrecy Motivating Problem Mixed Strategy Nondeterministic ID: 559025

total channel existence distribution channel total distribution existence analysis variation proof main reverse adversary memoryless joint constraints secrecy requirements simple distributionsrelax terms

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Slide1

Paul Cuff

The Source Coding Side of Secrecy

TexPoint fonts used in EMF.

Read the TexPoint manual before you delete this box.:

A

ASlide2

Game Theoretic Secrecy

Motivating Problem

Mixed Strategy

Non-deterministic

Requires randomdecoderDual to wiretap channel

Encoder

Communication

leakage

Eavesdropping

Zero-sum

Repeated

Game

Player 1

Player 2

StateSlide3

Main Topics of this Talk

Achievability Proof Techniques:

Pose

problems in terms of

existence of joint distributionsRelax Requirements to

“close in total variation”

Main Tool --- Reverse Channel EncoderEasy Analysis of Optimal AdversarySlide4

Restate Problem---Example 1 (RD Theory)

Can we design:

such that

Does there exists a distribution:

Standard

Existence of Distributions

f

gSlide5

Restate Problem---Example 2 (Secrecy)

Can we design:

such that

Does there exists a distribution:

Standard

Existence of Distributions

f

g

Eve

Score

[Cuff 10]Slide6

Tricks with Total Variation

Technique

Find a distribution

p

1 that is easy to analyze and satisfies the relaxed constraints.Construct p

2 to satisfy the hard constraints while maintaining small total variation distance to

p1.

How?

Property 1:Slide7

Tricks with Total Variation

Technique

Find a distribution

p

1 that is easy to analyze and satisfies the relaxed constraints.Construct p

2 to satisfy the hard constraints while maintaining small total variation distance to

p1.

Why?

Property 2 (bounded functions):Slide8

Summary

Achievability Proof Techniques:

Pose

problems in terms of

existence of joint distributionsRelax Requirements to “close in total variation”

Main Tool --- Reverse Channel Encoder

Easy Analysis

of Optimal AdversarySecrecy Example: For arbitrary

², does there exist a distribution satisfying:Slide9

Cloud Overlap Lemma

Previous EncountersWyner

, 75 --- used divergence

Han-

Verdú, 93 --- general channels, used total variationCuff 08, 09, 10, 11 --- provide simple proof and utilize for secrecy encoding

P

X|U

(

x|u

)

Memoryless

ChannelSlide10

Reverse Channel Encoder

For simplicity, ignore the key K, and consider

J

a

to be the part of the message that the adversary obtains. (i.e. J = (Ja,

Js), and ignore

Js for now)Construct a joint distribution between the source Xn

and the information Ja (revealed to the Adversary) using a memoryless channel.

P

X|U

(

x|u

)

Memoryless

ChannelSlide11

Simple Analysis

This encoder yields a very simple analysis and convenient properties

If |

J

a

| is large enough, then X

n will be nearly i.i.d. in total variationPerformance:

P

X|U

(

x|u

)

Memoryless

ChannelSlide12

Summary

Achievability Proof Techniques:

Pose

problems in terms of

existence of joint distributionsRelax Requirements to

“close in total variation”Main Tool ---

Reverse Channel EncoderEasy Analysis of Optimal Adversary