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Page 1: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Extractable Functions

Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen

Page 2: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Largest Known Prime

257,885,161 βˆ’ 1

Electronic Frontier Foundation offers $250,000 prize for a prime with at least a billion

digits

β€œThe first number larger then that is not divisible by any number other than 1 and itself”

Page 3: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Knowledge

Algorithm

Knowledge

Polynomial TimeExtraction Procedure

Page 4: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Proofs of Knowledge

𝑃 𝑉π‘₯βˆˆβ„’

Witness Extraction Hide the Witness

Secrecy : Zero-Knowledge \ Witness indistinguishability

Goal: Extract knowledge that is not publicly available

Page 5: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

CCA Encryption

𝐴𝑃𝐾𝐸𝑛𝑐 (𝑏)

𝑏

𝐷𝑒𝑐𝐸𝑛𝑐 (π‘₯)

π‘₯

ReductionTo CPA

Extractionπ‘₯

Page 6: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

More Knowledge

Zero-knowledge Proofs, Signatures, Non-malleable Commitments, Multi-party Computation, Obfuscation,…

𝐴Reduction

Extractionπ‘₯

Page 7: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

How to Extract?

Algorithm

Knowledge

Extraction?

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Extraction by Interaction

Or : Black-Box Extraction

Adversary Extraction

Public Parameters

Page 9: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Out of Reach Applications

𝑃 𝑉𝑃 𝑉

3-MessageZero-Knowledge

2-MessageSuccinct Argument

(SNARG)

Page 10: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Out of Reach Applications

𝑃 𝑉𝑃 𝑉

[Goldreich-Krawczyk][Gentry-Wichs]

Black-Box Security Proof is Impossible

Page 11: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Knowledge of Exponent

Adversary𝑔 , h

𝑔π‘₯ , hπ‘₯π‘₯ Extraction

[DamgΓ₯rd 92]

Non-Black-Box

Extraction

Page 12: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Applications of KEA

3-MessageZero-Knowledge

2-MessageSuccinct Argument

(SNARG)

Knowledge of Exponent Assumption* (KEA) *and

variants

[HT98,BP04,Mie08,G10,L12,BCCT13,GGPR13,BCIOP13]

Page 13: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Extractable Functions

Adversaryπ‘˜β†$

𝑓 π‘˜(π‘₯)π‘₯ Extraction

A family of function is extractable if:

[Canetti-Dakdouk 08]

Page 14: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Remarks on EF

β€’ KEA is an example for EF.

β€’ We want EF that are also one-

way.β€’ The image of should be

sparse.Adversary

π‘˜β†$

𝑓 π‘˜(π‘₯)π‘₯ Extraction

OWF, CRHF

Page 15: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Applications of EF

3-MessageZero-Knowledge

2-MessageSuccinct Argument(Privately Verifiable)

Knowledge of Exponent

Extractable One-Way Functions (EOWF)

Extractable Collision-Resistant Hash Functions (ECRH)

[BCCT12,GLR12,DFH12]

Page 16: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

What is missing?

β€’ Clean assumptions

β€’ Candidates

β€’ Strong applications

Page 17: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

A Reduction Using EF

𝐴Reduction

𝐸π‘₯

Assuming:

π‘˜β†$

𝑓 π‘˜(π‘₯)

Page 18: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Do Extractable One-

Way Functions with an Explicit Extractor

Exist?

Page 19: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

It depends on the Auxiliary Input.

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Example: Zero-Knowledge

𝑃 𝑉π‘₯βˆˆβ„’π‘˜π‘“ π‘˜ (𝑑 )

π‘₯

Auxiliary input

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Definition of EF with A.I.

For every and auxiliary inputthere exist and auxiliary inputsuch that for every auxiliary input :

Page 22: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Types of A.I.For every and auxiliary inputthere exist and auxiliary inputsuch that for every auxiliary input :

Individual \ CommonBounded \ Unbounded

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What type of A.I.

do we need?

Page 24: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Example: Zero-KnowledgeZero-Knowledge:For every there exists a simulator such that for every , For need bounded A.I.For sequential composition need unbounded A.I. What you get from individual A.I.:For every and every there exists a simulator such that

Page 25: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

PossibleImpossible Open

EOWF* with bounded A.I.:EOWF with unbounded common A.I.:

Subexp-LWEIndistinguishability Obfuscation

Explicit ExtractorDelegation for P from Subexp-PIR[Kalai-Raz-Rothblum13]

Page 26: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Generalized EOWF

EOWF* = Privately-Verifiable Generalized EOWF1. EOWF* suffices for applications of EOWF.2. The impossibility results holds also for EOWF* 3. Can remove * assuming publicly-verifiable delegation for P (P-certificates)

Page 27: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Application

3-Message Zero-KnowledgeEOWF

3-Message Zero-Knowledge

For verifiers w. bounded A.I .

EOWF withbounded

A.I.

EOWF* withbounded

A.I.

β‡’

β‡’

β‡’

[BCCGLRT13]

Page 28: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Construction

Survey

Impossibility

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Construction

EOWF* with Bounded A.I fromPrivately-Verifiable Delegation for P

EOWF with Bounded A.I fromPublicly-Verifiable Delegation for P

Page 30: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

First Attempt

β€’ OWF

β€’ Extraction from (no restriction on space or running time)

β€’ Single function - No key (impossible for unbounded A.I)

Page 31: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

First Attempt

𝑓 (𝑖 , 𝑠)=ΒΏ

𝑖 ,π‘ βˆˆ {0 ,1 }𝑛 , PRG: {0 ,1 }𝑛→ {0 ,1 }𝑛

Page 32: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

First Attempt

𝑓 (𝑖 , 𝑠)={PRG (𝑠)     if    𝑖≠0𝑛

𝑠 (1𝑛 ) if 𝑖=0𝑛

𝑖 ,π‘ βˆˆ {0 ,1 }𝑛 , PRG: {0 ,1 }𝑛→ {0 ,1 }𝑛

Interpert as a program outputting bits

Page 33: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Extraction

𝐴 (1𝑛)β†’ 𝑦

𝑓 (𝑖 , 𝑠)={PRG (𝑠 )     if    𝑖≠0𝑛

𝑠 (1𝑛 ) if 𝑖=0𝑛

𝐸 (1𝑛 )β†’0𝑛 , 𝐴

𝑓 (0𝑛 ,𝐴 )=𝐴 (1𝑛)=𝑦

()

Page 34: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

One-Wayness

𝑓 (𝑖 , 𝑠)={PRG (𝑠 )     if    𝑖≠0𝑛

𝑠 (1𝑛 ) if 𝑖=0𝑛

1. The image of is sparse

Page 35: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Problem

is not poly-time computable!

𝑓 (𝑖 , 𝑠)={𝑃 𝑅𝐺𝑠 (𝑠 )     if    𝑖≠0𝑛

𝑠 (1𝑛) if 𝑖=0𝑛

Solution: Delegation for P(following the protocols of

[B01,BLV03])

Page 36: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Delegation for P

𝑃 𝑉Gen ($ )β†’πœŽ

poly (𝑇𝑀 ) polylog (𝑇𝑀 )<𝑛

πœ‹ :𝑀 (1𝑛)β†’ 𝑦

Page 37: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Final Construction

𝑓 (𝑖 , 𝑠 ,π‘Ÿ , π‘¦βˆ— ,𝜎 βˆ— ,πœ‹βˆ—)

𝑖=0𝑛𝑖≠0𝑛

Output:

If is a valid proof for under Output:

Page 38: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Extraction

𝐴 (1𝑛)β†’(𝑦 ,𝜎 )

When is a proof that under

𝐸 (1𝑛 )β†’(0𝑛 ,𝐴 ,π‘Ÿ , 𝑦 ,𝜎 ,πœ‹βˆ—)

𝑓

Page 39: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

One-Wayness

1. The image of is sparse

2. Soundness of delegation

Page 40: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Generalized EOWF𝑅 ( 𝑓 (π‘₯ ) ,π‘₯ β€² )Hardness: For a random it is hard to find

Extraction:For every there exists such that

Privately-Verifiable GEOWF:Can efficiently test only given

Page 41: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Impossibility

Assuming indistinguishability obfuscation,

there is not EOWF with unbounded common auxiliary input

Page 42: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Intuition

Adversary π‘˜π‘“ π‘˜ (π‘₯ )π‘₯ AdversaryNon-Black-

Box Extractor

Common A.I Universal ExtractorThere exists s.t. for every and :

Page 43: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Plan

1. Assuming virtual black-box obfuscation [Goldreich, Hada-Tanaka]

2. Assuming indistinguishability obfuscation

Page 44: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Common A.I.

π΄π‘˜ ,𝑧

𝑓 π‘˜(π‘₯)

π‘₯𝐸

Page 45: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Universal Extraction

𝑓 π‘˜(π‘₯)

π‘₯Universa

l Extracto

r

π‘˜ ,𝑧=¿𝐴

Universal Adversaryπ΄π‘˜

Page 46: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Black-Box Extraction

𝑓 π‘˜(π‘₯)

π‘₯Universa

l Extracto

r

π‘˜ ,𝑧=¿𝐴

Universal Adversaryπ‘˜ 𝐴

Black-box obfuscation

Page 47: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Black-Box Extraction

Black-Box Extractor

π‘˜Adversary

π‘₯π‘˜=𝑃𝑅𝐹 𝑠(π‘˜) 𝑓 π‘˜(π‘₯π‘˜)π‘₯π‘˜

Adversary

π‘₯π‘˜=π‘ˆπ‘›

Page 48: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Indistinguishability Obfuscation

𝐢1𝐢2 ≑

Compute the same function

Page 49: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Indistinguishability Obfuscation

Extractor

π‘˜Adversary

π‘₯π‘˜=𝑃𝑅𝐹 𝑠(π‘˜) 𝑓 π‘˜(π‘₯π‘˜)π‘₯π‘˜

Prove that the obfuscation hides

Page 50: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Indistinguishability Obfuscation

Extractor

π‘˜ π‘₯π‘˜=𝑃𝑅𝐹 𝑠(π‘˜) 𝑓 π‘˜(π‘₯π‘˜)π‘₯π‘˜

Extractor

π‘˜ 𝑓 π‘˜(π‘₯π‘˜)π‘₯π‘˜

β‰ˆ

hides Alternative adversary

Page 51: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Alternative Adversary Using the Sahai-Waters puncturing technique

𝑃𝑅𝐹 𝑠 𝑓 π‘˜

π‘˜ 𝑓 π‘˜(π‘₯π‘˜)

Page 52: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Indistinguishability Obfuscation

Extractor

π‘˜ 𝑓 π‘˜(π‘₯π‘˜)π‘₯π‘˜

hides

Page 53: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Back to the Construction?

Page 54: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

PossibleImpossible Open

EOWF withunbounded individual A.I. Extractable CRHF\COM\1-to-1 OWF

Page 55: Nir Bitansky, Ran Canetti, Omer Paneth, Alon Rosen.

Thank You