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Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth Jaggi

Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

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Page 1: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Resilient Network Coding in the presence of Byzantine Adversaries

Michelle Effros

Michael Langberg

Tracey Ho

Sachin Katti

Muriel Médard

Dina Katabi

Sidharth Jaggi

Page 2: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Obligatory Example/Historys

t1 t2

b1 b2

b2

b2

b1

b1 b1

b1 b1

b1 (b1,b2)

b1+b2

b1+b2b1+b2

(b1,b2)

[ACLY00] [ACLY00] Characterization Non-constructive

[LYC03], [KM02] Constructive (linear) Exp-time design

[JCJ03], [SET03] Poly-time design Centralized design

[HKMKE03], [JCJ03] Decentralized design

EVER

BETTER

.

.

.

C=2

[This work] All the above, plus security

Tons of work

[SET03] Gap provably exists

Page 3: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Multicast

Simplifying assumptions• All links unit capacity

•(1 packet/transmission)• Acyclic network

ALL of Alice’sinformationdecodableEXACTLYbyEACH Bob

Network Model

[GDPHE04],[LME04] – No intereference

Page 4: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Multicast Network Model

ALL of Alice’sinformationdecodableEXACTLYbyEACH Bob

3

2

2

Upper bound for multicast capacity C,

C ≤ min{Ci}

[ACLY00] With mixing, C = min{Ci} achievable!

[LCY02],[KM01],[JCJ03],[HKMKE03] Simple (linear) distributed codes suffice!

Page 5: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Problem!

Eavesdropped links

Attacked links

Corrupted links

Page 6: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Setup

1. Scheme A B C2. Network

C3. Message A C4. Code C5. Bad links C6. Coin A7. Transmit B C8. Decode B

Eureka

Eavesdropped links ZI

Attacked links ZO

Who knows what

Stage

Privacy

Page 7: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

ResultsFirst codes Optimal rates (C-2ZO,C-ZO) Poly-time Distributed Unknown topology End-to-end Rateless Information theoretically secure Information theoretically private Wired/wireless

[HLKMEK04],[JLHE05],[CY06],[CJL06],[GP06]

Page 8: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Error Correcting Codes

Y=TX+E

Generator matrix

Low-weightvector

YX

(Reed-Solomon Code)

1

0

0

0

0

c

T

E R=C-2ZO

Page 9: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Alice: Sends packets.

Bob gets (Each column encoded with same transform T)

Now Bob knows T and can decode.

Distributed multicastA

B2

X I

TX T

C packets

“Small” rate-loss

[HKMKE03]

Page 10: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

What happens when we implement previous distributed algorithm?

Key idea: think of Calvin's error as an addition to original information flow.

Alice:

Calvin:

Bob:C packets

ZO packets

What happens with errors?

X I

TX T+T’E1 +T’E2

E1 E2

Bob:

•T,T’ are unknown.

•E1,E2 are unknown.

•System is not linear.

•How can Bob recover

X?

R packets

Page 11: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Alice:

Calvin:

Bob:

Overview

B1B2

X I

TX T

Calvin

+T’E1 +T’E2

E1 E2

Step 1: Show how to construct system of

linear equations to help recover X.

Step 2: System may have many solutions.

Need to add redundancy to X.

Step 1: “list decoding” will work as long as R ≤

C-ZO.

Step 2: “unique decoding” will need an additional redundancy of

ZO.

All in all: R = C-2ZO.

X+

= T’(E1-E2X)

Page 12: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Alice:

Calvin:

Bob:

+T’E2+T’E1

Properties of X I

E1 E2

X+

•Col. in X+.

= col. of X + col. of .

•Claim 1: has column rank ZO (=Calvin's strength).

•Proof: Follows from fact that Calvin controls ZO links.

•Claim 2: Columns of X and span disjoint spaces.

•Proof:R≤C-ZO, random encoding.

TTX

=+ =

R

ZO

C

Page 13: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

Theorems

Scheme achieves rate C-2ZO (optimal)

Step 1: list decode (R ≤ C-ZO)

Step 2: unique decode (Redundancy = ZO) Secret channel: Instead of Step 2, send hash of

X. Rate = C-ZO (optimal) Limited Adversary: Calvin limited in

eavesdropping – can implement secret channel and obtain rate C-ZO.

Limited eavesdropping:

•Calvin can only see the information on ZI links

•If ZI<C-ZO=R, can implement a secret channel [JL07]

Page 14: Resilient Network Coding in the presence of Byzantine Adversaries Michelle Effros Michael Langberg Tracey Ho Sachin Katti Muriel Médard Dina Katabi Sidharth

SummaryRate Conditions

Thm 1 C-ZO Secret

Thm 2 C-2ZO Omniscient

Thm 3 C-ZO Limited

Optimal rates Poly-timeDistributedUnknown topologyEnd-to-endRatelessInformation theoretically secure/privateWired/wireless