secure efficient multiparty computing of multivariate polynomials and applications

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Secure Efficient Multiparty Computing of Multivariate Polynomials and Applications. Dana Dachman-Soled, Tal Malkin, Mariana Raykova , Moti Yung. x 1. x 2. x 3. x 4. x 1. F 1 (x 1 ,x 3 ,x 3 ). x 2. x 3. F 2 (x 1 ,x 3 ,x 3 ). F 4 (x 1 ,x 3 ,x 3 ). x 4. F 3 (x 1 ,x 3 ,x 3 ). - PowerPoint PPT Presentation

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Secure Efficient Multiparty Computing of Multivariate Polynomials and

Applications

Dana Dachman-Soled, Tal Malkin,Mariana Raykova, Moti Yung

2

x1

x2

x3

x4

3

x1

x2

x3

x4

F1(x1,x3,x3)

F2(x1,x3,x3)

F3(x1,x3,x3)

F4(x1,x3,x3)

4

Secure Multiparty Computation

How to compute a function on the private inputs of multiple parties not leaking more than the result?

Secure Multiparty Computation

How to compute a function on the private inputs of multiple parties not leaking more than the result?

5

Secure Multiparty Computation

Feasible – [Yao82], [GMW87], [CDv88], [BG89], [BG90], [Cha90], [Bea92], …

Not Efficient – communication and computation proportional to circuit size

Secure Multiparty Computation

Feasible – [Yao82], [GMW87], [CDv88], [BG89], [BG90], [Cha90], [Bea92], …

Not Efficient – communication and computation proportional to circuit size

6

x1

x2

x3

x4

Multivariate Polynomials

7

x1

x2

x3

x4

Multivariate Polynomials

Applications

8

x1

x2

x3

x4

Multivariate Polynomials

Applications

MultipartySet Intersection

9

x1

x2

x3

x4

Multivariate Polynomials

Applications

Linear Algebra matrix arithmetic, inverse, determinant, Eigen values

10

x1

x2

x3

x4

Multivariate Polynomials

Applications

Statistics functions average, standard deviation, variance, chi-square test, computing Pearson’s correlation coefficients

11

x1

x2

x3

x4

Multivariate Polynomials

Applications

Taylor series approximation trigonometric functions, logarithms, exponents, square root

12

Outsourced computation• many workers• at least one honest

13

Outsourced computation•Computation on shares,•Reconstruction of output

Our results

• Multiparty computation protocol for functionalities that can be represented as multivariate polynomials– Improvement of generic complexity for multiple parties Left

as open problem in FM10• Security:

– Against malicious majority – Proofs in the standard simulation model

• Black box construction from homomorphic encryption with a natural property….– Instantiated through threshold Paillier encryption (decisional

composite residuosity)

14

Our Results

• Efficiency:– Communication complexity – FM10 subexponential in the

number of parties, we achieve fully polynomial (in all parameters) complexity:

• Broadcast complexity• Round table complexity

– Constant number round table rounds• Application construction: Multiparty Set Intersection

– Improve complexity of existing multiparty solutions KS05, SS09, CJS10

15

Building Blocks

• Input sharing using committed Shamir/Reed-Solomon codes

PX(0) = X shares PX(1), …, PX(D)• Vector Homomorphic Encryption

ENC(m1; r1) ENC(m⊗ 2; r2) = ENC(m1 + m2; r1 r⊕ 2)ENC(m; r)c = ENC(c · m; r c)⊙

– Instantiation: threshold Paillier encryption

16

Building Blocks

• Polynomial code commutativityInterpolate (Poly-Eval (inputs shares)) =Poly-Eval (Interpolate (inputs shares)) = Poly-Eval(inputs)

• Incremental encrypted polynomial evaluation– Each monomial M = c i=1 hi(inputs of party i)

– b0 = ; = ⊕

17

bi+1bi+1Enc(c)Enc(c) bibi hi(inputs of party i)hi(inputs of party i)

#parties

Encryption of partial evaluation of M with inputs from first i+1/i parties

Constant for homomorphic property

Building blocks• Lagrange Interpolation Protocol Over Encrypted Values:

– given A > d+1 encrypted points(1, ENCpk(y1, r1)), . . . (A, ENCpk(yA, rA))

– check that they lie on poly of degree dENCpk(yi,ri) = j=1 (ENCpk(yj,rj)) Lj(i)

– synchronized randomness• Randomness Interpolation

– given (1,y1),...,(A,yA),r1,...,rd+1

– compute rd+2, . . . , rA

– Encrypted interpolation holds for [i, ENCpk(yi, ri)]1≤i≤A

d+1

18

Efficient Input Preprocessing

• Polynomial Degree Reduction• Change of variables• Polynomial Q(y) of degree n

Q(y)Q(y) Q(y0,y1,y2 …, ylog n )Q(y0,y1,y2 …, ylog n )

y0 = yy1 = y2

y2 = y4

……….

ylog n = y2log n

Deg: n Deg: log n

y

19

Proof of Knowledge and Verification

• Correct computation of new variables• Correct degree of input sharing polynomials

Prover: x1,…,xn

Common: c1,…,cn, L(x1,…,xn) L ci = ENC(xi)

Input Proof Output

Verifier: Accept/Reject

enc(r1)enc(r1) enc(r2)enc(r2) enc(rn)enc(rn)

c1 * enc(r1)c1 * enc(r1) c2 * enc(r2)c2 * enc(r2)… cn * enc(rn)cn * enc(rn) (x1+r1,…,xn+rn) L

(r1,…,rn) L

open

0

1

ci * enc(ri) = enc(xi+ri) 20

Protocol Outline

21

• Efficient preprocessing for each variable in the multivariate polynomial

• Commit to shares of new variables

22

• Each party Pi contributes his inputs – in each monomial s for each share j

= ·

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bi+1,j,sbi+1,j,s bi,j,s h⊕ i(share j of Pi)bi,j,s h⊕ i(share j of Pi) Enc(0, ri,j,s)Enc(0, ri,j,s)

ri,j,s generated with randomness interpolation protocol

• Each party re-randomizes the final output shares S1, …, S10kD

– Randomizng polynomial Pj,0(0) = 0

– Shares (1,Pj,0(1)),...,(10kD,Pj,0(10kD))

– Re-randomized output shares = ·

24

S’i S’i Si Si j=1 ENCpk(Pj,0(i);rj,i)j=1 ENCpk(Pj,0(i);rj,i)m

rj,kD+2,...,rj,10kD generated with randomness interpolation protocol

• All parties verify that the encrypted output shares Si lie on a polynomial of degree kD

• Parties select a subset of the shares of size k and decommit corresponding shares

• Parties verify the computation of the open shares

25

P1(1)P1(1)

P2(1)P2(1)

Com(P1(2))Com(P1(2))

Com(P2(2))Com(P2(2))

Com(P1(3))Com(P1(3))

Com(P2(3))Com(P2(3))

P1(1)P1(1)

P2(4)P2(4)

Com(P1(10kD))Com(P1(10kD))

Com(P2(10kD))Com(P2(10kD))

Verify computation

Verify computation

Verify degree

Verify degree

• The parties run threshold decryption for each of the output shares

• The output receiver interpolates the output value from the shares

26

Protocol Complexities• Amortized – sharing with multiple secrets• Communication complexity

– Round table – between consecutive parties: intermediate protocol messages

• O(Dn(m-1)), m parties, n monomials, D sum of log variable degrees– Broadcast – input commitments, decommitments in

verification phase• Smaller than polynomial representation• O(D (j=1 j=1 log αj,t ))• αj,t highest degree of variable, Lj inputs for party j

• Computational complexity• O(Dnm)

m Lj

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Multiparty set intersection = · +

• Optimizations:– Only two parties have inputs per each monomial– Inputs that are used only once do not need to be shared• Complexity - m parties, d inputs each:– Communication - O(md + 10d log2 d); CJS10 – quadratic in

number of parties, other solutions worse complexity– Computation - O(md2 log d)

28

P(x) P(x) ri ri Pi(x)Pi(x) x x

ri = ri,1 + … + ri,m

ri,j randomness from party j

Pi(x) represents the input set of party i

j=1 j=1

m-1

Thank You!

• Questions?

29

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