SlideShare uma empresa Scribd logo
1 de 114
Baixar para ler offline
Caulk: Lookup
Arguments
in Sublinear Time
Vitalik Buterin
Dmitry Khovratovich
Arantxa Zapico Mary Maller Anca Nitulescu
Mark Simkin
Universitat Pompeu Fabra Ethereum Foundation Protocol Labs
MOTIVATION
MEMBERSHIP PROOFS
pk1
pk2
pk3
pk4
pk5
pk6
pk7
pk8
pk9
pk10
MEMBERSHIP PROOFS
pk3
pk4
pk5
pk6
pk7
pk8
pk9
pk10
pk1
pk2
MEMBERSHIP PROOFS
pk3
pk4
pk5
pk6
pk7
pk8
pk9
pk10
pk1
pk2
sk2
RANGE PROOFS
RANGE PROOFS
RANGE PROOFS
N1
N2
N
LOOKUP TABLES
LOOKUP TABLES
LOOKUP TABLES
STATE OF THE ART
STATE OF THE ART
Discrete-log
STATE OF THE ART
Transparent setup
Linear prover and
verifier
Discrete-log
STATE OF THE ART
Transparent setup
Linear prover and
verifier
RSA Accumulators
Discrete-log
STATE OF THE ART
Transparent setup
Linear prover and
verifier
RSA Accumulators
Discrete-log
Constant prover
Trusted parameters
STATE OF THE ART
Transparent setup
Linear prover and
verifier
Merkle Trees
RSA Accumulators
Discrete-log
Constant prover
Trusted parameters
STATE OF THE ART
Transparent setup
Linear prover and
verifier
Merkle Trees
RSA Accumulators
Discrete-log
Transparent setup
Need a zkSNARK on top
Constant prover
Trusted parameters
STATE OF THE ART
Pairing-based
Transparent setup
Linear prover and
verifier
Merkle Trees
RSA Accumulators
Discrete-log
Transparent setup
Need a zkSNARK on top
Constant prover
Trusted parameters
STATE OF THE ART
Pairing-based
Transparent setup
Linear prover and
verifier
Merkle Trees
RSA Accumulators
Discrete-log
Constant proof +
verifier
Linear prover
Transparent setup
Need a zkSNARK on top
Constant prover
Trusted parameters
CAULK
Pairing-based
CAULK
Pairing-based
Logaritmic prover + constant proof
log(log) verifier
DEFINITION
DEFINITION
DEFINITION
Everything in
is also in
Position-hiding linkability for two VC schemes
KZG
KZG
(v1
,…,vN
)
KZG
(v1
,…,vN
)
KZG
(v1
,…,vN
)
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
KZG
(v1
,…,vN
)
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
{λi
(X)} , λi
(⍵i-1
)=1, λi
(⍵j
)=0
KZG
C(X)=Σi
vi
λi
(X)
(v1
,…,vN
)
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
{λi
(X)} , λi
(⍵i-1
)=1, λi
(⍵j
)=0
KZG
C(X)=Σi
vi
λi
(X) C(⍵i-1
)=vi
(v1
,…,vN
)
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
{λi
(X)} , λi
(⍵i-1
)=1, λi
(⍵j
)=0
ROOTS OF UNITY
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
ROOTS OF UNITY
1. Sparse Lagrange and vanishing polynomials
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
ROOTS OF UNITY
1. Sparse Lagrange and vanishing polynomials
zH
(X)=XN
-1 λi
(X)= (⍵i-1
(XN
-1)) ((X-⍵i-1
)N)-1
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
ROOTS OF UNITY
1.
2.
Sparse Lagrange and vanishing polynomials
Any u such that uN
=1 is an Nth root of unity
zH
(X)=XN
-1 λi
(X)= (⍵i-1
(XN
-1)) ((X-⍵i-1
)N)-1
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
ROOTS OF UNITY
1.
2.
Sparse Lagrange and vanishing polynomials
Any u such that uN
=1 is an Nth root of unity
zH
(X)=XN
-1 λi
(X)= (⍵i-1
(XN
-1)) ((X-⍵i-1
)N)-1
H={1,⍵,⍵2
,…,⍵N-1
}, ⍵N
=1
If uN
=1 u=⍵something
KZG + TABDFK
KZG + TABDFK
C(X)=Σi
vi
λi
(X)
KZG + TABDFK
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Prover sends [CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Prover sends [CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
CI
(X)=ΣiƐ I
vi
τi
(X)
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Prover sends [CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
CI
(X)=ΣiƐ I
vi
τi
(X)
HI
={⍵i-1
}iƐ I
KZG + TABDFK
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Prover sends [CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
KZG + TABDFK
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Prover sends [CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
Verifier checks
e([C(x)], [CI
(x)])=e([ΠiƐ I
(x-⍵i-1
)],[QI
(x)])
KZG + TABDFK
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
C(X)-vi
=(X-⍵i-1
)Qi
(X)
Qi
(X) and QI
(X) are linear in N!!!
C(X)=Σi
vi
λi
(X)
Prover sends [vi
],[(x-⍵i-1
)],[Qi
(x)]
s.t:
Prover sends [CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)]
s.t:
Verifier checks
e([C(x)],[vi
])=e([(x-⍵i-1
)],[Qi
(x)])
Verifier checks
e([C(x)], [CI
(x)])=e([ΠiƐ I
(x-⍵i-1
)],[QI
(x)])
KZG + TABDFK
Precompute ([Q1
(x)],...,[QN
(x)])
KZG + TABDFK
Precompute ([Q1
(x)],...,[QN
(x)])
C(X)-vi
=(X-⍵i-1
)Qi
(X)
KZG + TABDFK
Precompute ([Q1
(x)],...,[QN
(x)])
C(X)-vi
=(X-⍵i-1
)Qi
(X)
KZG + TABDFK
Precompute ([Q1
(x)],...,[QN
(x)])
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
KZG + TABDFK
{Qi
(X)}iƐ I
Precompute ([Q1
(x)],...,[QN
(x)])
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
KZG + TABDFK
{Qi
(X)}iƐ I
Precompute ([Q1
(x)],...,[QN
(x)])
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
KZG + TABDFK
{Qi
(X)}iƐ I QI
(X)=ΣiƐI
ki
Qi
(X)
Precompute ([Q1
(x)],...,[QN
(x)])
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
KZG + TABDFK
C(X)-vi
=(X-⍵i-1
)Qi
(X)
C(X)-CI
(X)=ΠiƐ I
(X-⍵i-1
) QI
(X)
{Qi
(X)}iƐ I
Prover depends
on |I|=m
QI
(X)=ΣiƐI
ki
Qi
(X)
Precompute ([Q1
(x)],...,[QN
(x)])
KZG + TABDFK
C(X)=Σi
vi
λi
(X) is public
proofI
=([CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)])
proofi
=([vi
],[(x-⍵i-1
)],[Qi
(x)])
KZG + TABDFK
C(X)=Σi
vi
λi
(X) is public
proofI
=([CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)])
proofi
=([vi
],[(x-⍵i-1
)],[Qi
(x)])
Blind vi
,CI
(X)
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind vi
,CI
(X)
proofI
=([CI
(x)+zI
(x)s(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)])
proofi
=([vi
+hr],[(x-⍵i-1
)],[Qi
(x)])
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind vi
,CI
(X)
proofI
=([a],[ΠiƐ I
(x-⍵i-1
)],[QI
(x)])
proofi
=([a],[(x-⍵i-1
)],[Qi
(x)])
KZG + TABDFK
C(X)=Σi
vi
λi
(X) is public
proofI
=([CI
(x)],[ΠiƐ I
(x-⍵i-1
)], [QI
(x)])
proofi
=([vi
],[(x-⍵i-1
)],[Qi
(x)])
Blind Qi
(X),QI
(X)
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind Qi
(X),QI
(X)
proofI
=([a],[ΠiƐ I
(x-⍵i-1
)],[r1
-1
QI
(x)+r(x)])
proofi
=([a],[(x-⍵i-1
)],[Qi
(x)+sh)])
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind vi
,CI
(X)
Blind Qi
(X),QI
(X)
proofI
=([a],[ΠiƐ I
(x-⍵i-1
)],[QI
])
proofi
=([a],[(x-⍵i-1
)],[Qi
])
KZG + TABDFK
C(X)=Σi
vi
λi
(X) is public
proofI
=([CI
(x)],[ΠiƐ I
(x-⍵i-1
)],[QI
])
proofi
=([vi
],[(x-⍵i-1
)],[Qi
])
Blind ,(X-⍵i-1
),ΠiƐ I
(X-⍵i-1
)
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind ,(X-⍵i-1
),ΠiƐ I
(X-⍵i-1
)
proofI
=([a],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
proofi
=([a],[a(x-⍵i-1
)],[Qi
])
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind vi
,CI
(X)
Blind Qi
(X),QI
(X)
Blind ,(X-⍵i-1
),ΠiƐ I
(X-⍵i-1
)
proofI
=([a],[zI
],[QI
])
proofi
=([a],[z],[Qi
])
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind vi
,CI
(X)
Blind Qi
(X),QI
(X)
Blind ,(X-⍵i-1
),ΠiƐ I
(X-⍵i-1
)
proofI
=([a],[zI
],[QI
])
proofi
=([a],[z],[Qi
])
Well formation
C(X)=Σi
vi
λi
(X) is public
CHALLENGES
Blind vi
,CI
(X)
Blind Qi
(X),QI
(X)
Blind ,(X-⍵i-1
),ΠiƐ I
(X-⍵i-1
)
Well formation
proofI
=([a],[zI
],[QI
])
proofi
=([a],[z],[Qi
])
[z]=[a(x-⍵i-1
)]
Well formation
m=1
[z]=[a(x-⍵i-1
)]
1
2
3
4
Well formation
m=1
[z]=[a(x-⍵i-1
)]
1
2
3
4
Well formation
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
New set of roots of unity! V
Lagrange polynomials {µj
(X)}
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
Prove f5
=b/a, and for j = 6,...,log(N)+5 fj
=fj-1
fj-1
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
Prove f5
=b/a, and for j = 6,...,log(N)+5 fj
=fj-1
fj-1
Should be ⍵i-1
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
Should be ⍵i-1
f5+j
is the 2j
th power
of ⍵i-1
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
Prove f5
=b/a, and for j = 6,...,log(N)+5 fj
=fj-1
fj-1
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
Prove flog(N)+5
=1
m=1
Prove [z]=[ax+b] (b=a⍵i-1
)
Prove f5
=b/a, and for j = 6,...,log(N)+5 fj
=fj-1
fj-1
[z]=[a(x-⍵i-1
)]
1
2
3
4
Construct f(X) of degree log(N)+6,
f(X)=Σj
fj
µj
(X)
Well formation
Prove flog(N)+5
=1
(b/a)N
=1 !!!
Prove [z]=[ax+b] (b=a⍵i-1
)
m=1
Prove f5
=b/a, and for j = 6,...,log(N)+5 fj
=fj-1
fj-1
m>1
proofI
=([CI
(x)],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
m>1
proofI
=([ΠiƐ I
vi
τi
(x)],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
m>1
HI
={⍵i-1
}iƐ I
proofI
=([ΠiƐ I
vi
τi
(x)],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
m>1
HI
={⍵i-1
}iƐ I
“I” unknown to the verifier!
proofI
=([ΠiƐ I
vi
τi
(x)],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
m>1
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
proofI
=([ΠiƐ I
vi
τi
(x)],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
m>1
aj
=vi
for some i,for all j
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
proofI
=([ΠiƐ I
vi
τi
(x)],[r1
ΠiƐ I
(x-⍵i-1
)],[QI
])
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u=(⍵i-1
)iƐ I
but with repetitions
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
The roots used in zI
with
repetitions
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
=us-1
us-1
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
The coeficients in us
(X) are the 2s
power of the uj
s
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
The coeficients in us
(X) are the 2s
power of the uj
s
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
3. Prove ulog(N)
=(1,1,…,1)
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
3. Prove ulog(N)
(X)=Σ1µj
(x)
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
3. Prove ulog(N)
(X)=Σ1µj
(x)
All the 2log(N)
th powers of the uj
s are 1!
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
1. Set u(X)=Σ⍵i-1
µj,i
(x)=Σuj
µj
(x)
2. Compute us
(X)=us-1
(X)us-1
(X) mod zV
(X)
3. Prove ulog(N)
(X)=Σ1µj
(x)
All the Nth powers of the uj
s are 1!
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([zI
(⍵something
)],[1])= e([0],[Q2
])
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([zI
(⍵something
)],[1])= e([0],[Q2
])
[zI
] is well formed
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([C(x)]-[CI
])= e([QI
],[zI
])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([C(⍵something
)]-[CIsomething
])= e([QI
],[0])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([vsomething
]-[CIsomething
])= e([QI
],[0])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[CI
] contains a subvector of v
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([C(x)]-[CI
])= e([QI
],[zI
])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
e([CI
(u(x))]- [ϕ(x)],[1])= e([zV
],[Q3
])
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04
e([C(x)]-[CI
])= e([QI
],[zI
])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
e([CI
(⍵something
)]- [aj
],[1])= e([0],[Q3
])
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04 e([vsomething
)]- [aj
],[1])= [0]
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
e([C(x)]-[CI
])= e([QI
],[zI
])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04 e([vsomething
)]- [aj
],[1])= [0]
Everyting in a is also in v
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
e([C(x)]-[CI
])= e([QI
],[zI
])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
m>1
proofI
=([CI
],[zI
],[QI
])
[C(x)=Σi
vi
λi
(x) ],[ϕ(x)=Σj
aj
µj
(x)]
01
02
03
04 e([vsomething
)]- [aj
],[1])= [0]
Position-hiding linkability!!!
[u(x)] with Nth roots of unity as coefficients in {µj
(X)}
e([C(x)]-[CI
])= e([QI
],[zI
])
e([zI
(u(x))],[1])= e([zV
],[Q2
])
[zI
]=[r1
ΠiƐ I
(x-⍵i-1
)]
IMPLEMENTATION
IMPLEMENTATION
CREDITS: This presentation template was
created by Slidesgo,including icons by
Flaticon,infographics & images by Freepik
THANKS!
https://eprint.iacr.org/2022/621

Mais conteúdo relacionado

Mais procurados

Optcarrot: A Pure-Ruby NES Emulator
Optcarrot: A Pure-Ruby NES EmulatorOptcarrot: A Pure-Ruby NES Emulator
Optcarrot: A Pure-Ruby NES Emulatormametter
 
Rouault imbert alpc_rpc_pacsec
Rouault imbert alpc_rpc_pacsecRouault imbert alpc_rpc_pacsec
Rouault imbert alpc_rpc_pacsecPacSecJP
 
公開鍵暗号(3): 離散対数問題
公開鍵暗号(3): 離散対数問題公開鍵暗号(3): 離散対数問題
公開鍵暗号(3): 離散対数問題Joe Suzuki
 
HDL Implementation of CCSDS Standards by Jonatan Brodin Final Version
HDL Implementation of CCSDS Standards by Jonatan Brodin Final VersionHDL Implementation of CCSDS Standards by Jonatan Brodin Final Version
HDL Implementation of CCSDS Standards by Jonatan Brodin Final VersionJonatan Brodin
 
zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)
zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)
zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)Alex Pruden
 
「にじたい」へのいざない #ロマンティック数学ナイト
「にじたい」へのいざない #ロマンティック数学ナイト「にじたい」へのいざない #ロマンティック数学ナイト
「にじたい」へのいざない #ロマンティック数学ナイトJunpei Tsuji
 
LISA17 Container Performance Analysis
LISA17 Container Performance AnalysisLISA17 Container Performance Analysis
LISA17 Container Performance AnalysisBrendan Gregg
 
RSA暗号運用でやってはいけない n のこと #ssmjp
RSA暗号運用でやってはいけない n のこと #ssmjpRSA暗号運用でやってはいけない n のこと #ssmjp
RSA暗号運用でやってはいけない n のこと #ssmjpsonickun
 
32 stoke's theorem
32 stoke's theorem32 stoke's theorem
32 stoke's theoremmath267
 
Ôn tập.pdf
Ôn tập.pdfÔn tập.pdf
Ôn tập.pdfGiaLcTrn2
 
Guia de calculo 1 MATEMATICA
Guia de calculo 1 MATEMATICAGuia de calculo 1 MATEMATICA
Guia de calculo 1 MATEMATICAArmando Cavero
 
Trig cheat sheet
Trig cheat sheetTrig cheat sheet
Trig cheat sheetAneel Ahmad
 
【暗号通貨輪読会#14】confidential transaction
【暗号通貨輪読会#14】confidential transaction【暗号通貨輪読会#14】confidential transaction
【暗号通貨輪読会#14】confidential transactionshigeyuki azuchi
 
katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃
katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃
katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃trmr
 
プログラマのための線形代数再入門
プログラマのための線形代数再入門プログラマのための線形代数再入門
プログラマのための線形代数再入門Taketo Sano
 
SAT/SMT solving in Haskell
SAT/SMT solving in HaskellSAT/SMT solving in Haskell
SAT/SMT solving in HaskellMasahiro Sakai
 
x^2+ny^2の形で表せる素数の法則と類体論
x^2+ny^2の形で表せる素数の法則と類体論x^2+ny^2の形で表せる素数の法則と類体論
x^2+ny^2の形で表せる素数の法則と類体論Junpei Tsuji
 
rrxv6 Build a Riscv xv6 Kernel in Rust.pdf
rrxv6 Build a Riscv xv6 Kernel in Rust.pdfrrxv6 Build a Riscv xv6 Kernel in Rust.pdf
rrxv6 Build a Riscv xv6 Kernel in Rust.pdfYodalee
 

Mais procurados (20)

楕円曲線と暗号
楕円曲線と暗号楕円曲線と暗号
楕円曲線と暗号
 
Optcarrot: A Pure-Ruby NES Emulator
Optcarrot: A Pure-Ruby NES EmulatorOptcarrot: A Pure-Ruby NES Emulator
Optcarrot: A Pure-Ruby NES Emulator
 
Rouault imbert alpc_rpc_pacsec
Rouault imbert alpc_rpc_pacsecRouault imbert alpc_rpc_pacsec
Rouault imbert alpc_rpc_pacsec
 
公開鍵暗号(3): 離散対数問題
公開鍵暗号(3): 離散対数問題公開鍵暗号(3): 離散対数問題
公開鍵暗号(3): 離散対数問題
 
HDL Implementation of CCSDS Standards by Jonatan Brodin Final Version
HDL Implementation of CCSDS Standards by Jonatan Brodin Final VersionHDL Implementation of CCSDS Standards by Jonatan Brodin Final Version
HDL Implementation of CCSDS Standards by Jonatan Brodin Final Version
 
zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)
zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)
zkStudyClub - ProtoStar (Binyi Chen & Benedikt Bünz, Espresso Systems)
 
暗号技術入門
暗号技術入門暗号技術入門
暗号技術入門
 
「にじたい」へのいざない #ロマンティック数学ナイト
「にじたい」へのいざない #ロマンティック数学ナイト「にじたい」へのいざない #ロマンティック数学ナイト
「にじたい」へのいざない #ロマンティック数学ナイト
 
LISA17 Container Performance Analysis
LISA17 Container Performance AnalysisLISA17 Container Performance Analysis
LISA17 Container Performance Analysis
 
RSA暗号運用でやってはいけない n のこと #ssmjp
RSA暗号運用でやってはいけない n のこと #ssmjpRSA暗号運用でやってはいけない n のこと #ssmjp
RSA暗号運用でやってはいけない n のこと #ssmjp
 
32 stoke's theorem
32 stoke's theorem32 stoke's theorem
32 stoke's theorem
 
Ôn tập.pdf
Ôn tập.pdfÔn tập.pdf
Ôn tập.pdf
 
Guia de calculo 1 MATEMATICA
Guia de calculo 1 MATEMATICAGuia de calculo 1 MATEMATICA
Guia de calculo 1 MATEMATICA
 
Trig cheat sheet
Trig cheat sheetTrig cheat sheet
Trig cheat sheet
 
【暗号通貨輪読会#14】confidential transaction
【暗号通貨輪読会#14】confidential transaction【暗号通貨輪読会#14】confidential transaction
【暗号通貨輪読会#14】confidential transaction
 
katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃
katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃
katagaitai workshop #7 crypto ナップサック暗号と低密度攻撃
 
プログラマのための線形代数再入門
プログラマのための線形代数再入門プログラマのための線形代数再入門
プログラマのための線形代数再入門
 
SAT/SMT solving in Haskell
SAT/SMT solving in HaskellSAT/SMT solving in Haskell
SAT/SMT solving in Haskell
 
x^2+ny^2の形で表せる素数の法則と類体論
x^2+ny^2の形で表せる素数の法則と類体論x^2+ny^2の形で表せる素数の法則と類体論
x^2+ny^2の形で表せる素数の法則と類体論
 
rrxv6 Build a Riscv xv6 Kernel in Rust.pdf
rrxv6 Build a Riscv xv6 Kernel in Rust.pdfrrxv6 Build a Riscv xv6 Kernel in Rust.pdf
rrxv6 Build a Riscv xv6 Kernel in Rust.pdf
 

Semelhante a Caulk: zkStudyClub: Caulk - Lookup Arguments in Sublinear Time (A. Zapico)

Otter 2016-11-28-01-ss
Otter 2016-11-28-01-ssOtter 2016-11-28-01-ss
Otter 2016-11-28-01-ssRuo Ando
 
Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)
Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)
Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)Dahua Lin
 
Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space Eliezer Silva
 
Slides: Jeffreys centroids for a set of weighted histograms
Slides: Jeffreys centroids for a set of weighted histogramsSlides: Jeffreys centroids for a set of weighted histograms
Slides: Jeffreys centroids for a set of weighted histogramsFrank Nielsen
 
Probabilistic Control of Switched Linear Systems with Chance Constraints
Probabilistic Control of Switched Linear Systems with Chance ConstraintsProbabilistic Control of Switched Linear Systems with Chance Constraints
Probabilistic Control of Switched Linear Systems with Chance ConstraintsLeo Asselborn
 
Assignment properties of linear time-invariant systems
Assignment properties of linear time-invariant systemsAssignment properties of linear time-invariant systems
Assignment properties of linear time-invariant systemsPatrickMumba7
 
Ruslan Shevchenko - Property based testing
Ruslan Shevchenko - Property based testingRuslan Shevchenko - Property based testing
Ruslan Shevchenko - Property based testingIevgenii Katsan
 
A new approach in specifying the inverse quadratic matrix in modulo-2 for con...
A new approach in specifying the inverse quadratic matrix in modulo-2 for con...A new approach in specifying the inverse quadratic matrix in modulo-2 for con...
A new approach in specifying the inverse quadratic matrix in modulo-2 for con...Anax Fotopoulos
 
Introduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from ScratchIntroduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from ScratchAhmed BESBES
 
Sampled-Data Piecewise Affine Slab Systems: A Time-Delay Approach
Sampled-Data Piecewise Affine Slab Systems: A Time-Delay ApproachSampled-Data Piecewise Affine Slab Systems: A Time-Delay Approach
Sampled-Data Piecewise Affine Slab Systems: A Time-Delay ApproachBehzad Samadi
 
14 Bivariate Transformations
14 Bivariate Transformations14 Bivariate Transformations
14 Bivariate TransformationsHadley Wickham
 
Generating and Analyzing Events
Generating and Analyzing EventsGenerating and Analyzing Events
Generating and Analyzing Eventsztellman
 
DissertationSlides169
DissertationSlides169DissertationSlides169
DissertationSlides169Ryan White
 
Nikolay Shilov. CSEDays 3
Nikolay Shilov. CSEDays 3Nikolay Shilov. CSEDays 3
Nikolay Shilov. CSEDays 3LiloSEA
 
Classification of Uq(sl2)-module algebra structures on the quantum plane
Classification of Uq(sl2)-module algebra structures on the quantum planeClassification of Uq(sl2)-module algebra structures on the quantum plane
Classification of Uq(sl2)-module algebra structures on the quantum planeSteven Duplij (Stepan Douplii)
 
Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...
Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...
Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...Leo Asselborn
 
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...Leo Asselborn
 

Semelhante a Caulk: zkStudyClub: Caulk - Lookup Arguments in Sublinear Time (A. Zapico) (20)

Otter 2016-11-28-01-ss
Otter 2016-11-28-01-ssOtter 2016-11-28-01-ss
Otter 2016-11-28-01-ss
 
Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)
Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)
Appendix to MLPI Lecture 2 - Monte Carlo Methods (Basics)
 
Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space Locality-sensitive hashing for search in metric space
Locality-sensitive hashing for search in metric space
 
Slides: Jeffreys centroids for a set of weighted histograms
Slides: Jeffreys centroids for a set of weighted histogramsSlides: Jeffreys centroids for a set of weighted histograms
Slides: Jeffreys centroids for a set of weighted histograms
 
Probabilistic Control of Switched Linear Systems with Chance Constraints
Probabilistic Control of Switched Linear Systems with Chance ConstraintsProbabilistic Control of Switched Linear Systems with Chance Constraints
Probabilistic Control of Switched Linear Systems with Chance Constraints
 
Assignment properties of linear time-invariant systems
Assignment properties of linear time-invariant systemsAssignment properties of linear time-invariant systems
Assignment properties of linear time-invariant systems
 
Ruslan Shevchenko - Property based testing
Ruslan Shevchenko - Property based testingRuslan Shevchenko - Property based testing
Ruslan Shevchenko - Property based testing
 
A new approach in specifying the inverse quadratic matrix in modulo-2 for con...
A new approach in specifying the inverse quadratic matrix in modulo-2 for con...A new approach in specifying the inverse quadratic matrix in modulo-2 for con...
A new approach in specifying the inverse quadratic matrix in modulo-2 for con...
 
Microeconomics-Help-Experts.pptx
Microeconomics-Help-Experts.pptxMicroeconomics-Help-Experts.pptx
Microeconomics-Help-Experts.pptx
 
Introduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from ScratchIntroduction to Neural Networks and Deep Learning from Scratch
Introduction to Neural Networks and Deep Learning from Scratch
 
Abstract machines for great good
Abstract machines for great goodAbstract machines for great good
Abstract machines for great good
 
Sampled-Data Piecewise Affine Slab Systems: A Time-Delay Approach
Sampled-Data Piecewise Affine Slab Systems: A Time-Delay ApproachSampled-Data Piecewise Affine Slab Systems: A Time-Delay Approach
Sampled-Data Piecewise Affine Slab Systems: A Time-Delay Approach
 
14 Bivariate Transformations
14 Bivariate Transformations14 Bivariate Transformations
14 Bivariate Transformations
 
Generating and Analyzing Events
Generating and Analyzing EventsGenerating and Analyzing Events
Generating and Analyzing Events
 
DissertationSlides169
DissertationSlides169DissertationSlides169
DissertationSlides169
 
Nikolay Shilov. CSEDays 3
Nikolay Shilov. CSEDays 3Nikolay Shilov. CSEDays 3
Nikolay Shilov. CSEDays 3
 
Classification of Uq(sl2)-module algebra structures on the quantum plane
Classification of Uq(sl2)-module algebra structures on the quantum planeClassification of Uq(sl2)-module algebra structures on the quantum plane
Classification of Uq(sl2)-module algebra structures on the quantum plane
 
Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...
Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...
Control of Discrete-Time Piecewise Affine Probabilistic Systems using Reachab...
 
Disjoint sets
Disjoint setsDisjoint sets
Disjoint sets
 
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
 

Mais de Alex Pruden

zkStudyClub - zkSaaS (Sruthi Sekar, UCB)
zkStudyClub - zkSaaS (Sruthi Sekar, UCB)zkStudyClub - zkSaaS (Sruthi Sekar, UCB)
zkStudyClub - zkSaaS (Sruthi Sekar, UCB)Alex Pruden
 
zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)
zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)
zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)Alex Pruden
 
zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...
zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...
zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...Alex Pruden
 
Eos - Efficient Private Delegation of zkSNARK provers
Eos  - Efficient Private Delegation of zkSNARK proversEos  - Efficient Private Delegation of zkSNARK provers
Eos - Efficient Private Delegation of zkSNARK proversAlex Pruden
 
zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]
zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]
zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]Alex Pruden
 
zkStudy Club: Subquadratic SNARGs in the Random Oracle Model
zkStudy Club: Subquadratic SNARGs in the Random Oracle ModelzkStudy Club: Subquadratic SNARGs in the Random Oracle Model
zkStudy Club: Subquadratic SNARGs in the Random Oracle ModelAlex Pruden
 
ZK Study Club: Sumcheck Arguments and Their Applications
ZK Study Club: Sumcheck Arguments and Their ApplicationsZK Study Club: Sumcheck Arguments and Their Applications
ZK Study Club: Sumcheck Arguments and Their ApplicationsAlex Pruden
 
Ecfft zk studyclub 9.9
Ecfft zk studyclub 9.9Ecfft zk studyclub 9.9
Ecfft zk studyclub 9.9Alex Pruden
 
Quarks zk study-club
Quarks zk study-clubQuarks zk study-club
Quarks zk study-clubAlex Pruden
 
zkStudyClub: CirC and Compiling Programs to Circuits
zkStudyClub: CirC and Compiling Programs to CircuitszkStudyClub: CirC and Compiling Programs to Circuits
zkStudyClub: CirC and Compiling Programs to CircuitsAlex Pruden
 

Mais de Alex Pruden (10)

zkStudyClub - zkSaaS (Sruthi Sekar, UCB)
zkStudyClub - zkSaaS (Sruthi Sekar, UCB)zkStudyClub - zkSaaS (Sruthi Sekar, UCB)
zkStudyClub - zkSaaS (Sruthi Sekar, UCB)
 
zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)
zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)
zkStudyClub - Lasso/Jolt (Justin Thaler, GWU/a16z)
 
zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...
zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...
zkStudyClub - Improving performance of non-native arithmetic in SNARKs (Ivo K...
 
Eos - Efficient Private Delegation of zkSNARK provers
Eos  - Efficient Private Delegation of zkSNARK proversEos  - Efficient Private Delegation of zkSNARK provers
Eos - Efficient Private Delegation of zkSNARK provers
 
zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]
zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]
zkStudyClub: Zero-Knowledge Proofs Security, in Practice [JP Aumasson, Taurus]
 
zkStudy Club: Subquadratic SNARGs in the Random Oracle Model
zkStudy Club: Subquadratic SNARGs in the Random Oracle ModelzkStudy Club: Subquadratic SNARGs in the Random Oracle Model
zkStudy Club: Subquadratic SNARGs in the Random Oracle Model
 
ZK Study Club: Sumcheck Arguments and Their Applications
ZK Study Club: Sumcheck Arguments and Their ApplicationsZK Study Club: Sumcheck Arguments and Their Applications
ZK Study Club: Sumcheck Arguments and Their Applications
 
Ecfft zk studyclub 9.9
Ecfft zk studyclub 9.9Ecfft zk studyclub 9.9
Ecfft zk studyclub 9.9
 
Quarks zk study-club
Quarks zk study-clubQuarks zk study-club
Quarks zk study-club
 
zkStudyClub: CirC and Compiling Programs to Circuits
zkStudyClub: CirC and Compiling Programs to CircuitszkStudyClub: CirC and Compiling Programs to Circuits
zkStudyClub: CirC and Compiling Programs to Circuits
 

Último

Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxKatpro Technologies
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessPixlogix Infotech
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?Igalia
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processorsdebabhi2
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsEnterprise Knowledge
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 

Último (20)

Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Advantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your BusinessAdvantages of Hiring UIUX Design Service Providers for Your Business
Advantages of Hiring UIUX Design Service Providers for Your Business
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
IAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI SolutionsIAC 2024 - IA Fast Track to Search Focused AI Solutions
IAC 2024 - IA Fast Track to Search Focused AI Solutions
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 

Caulk: zkStudyClub: Caulk - Lookup Arguments in Sublinear Time (A. Zapico)