hard instances of the constrained discrete logarithm problem ilya mironovmicrosoft research anton...

31
Hard Instances of the Constrained Discrete Logarithm Problem Ilya Mironov Microsoft Research Anton Mityagin UCSD Kobbi Nissim Ben Gurion University Speaker: Ramarathnam Venkatesan (Microsoft Research)

Upload: alyssa-mackay

Post on 26-Mar-2015

218 views

Category:

Documents


2 download

TRANSCRIPT

Page 1: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Hard Instances of the Constrained DiscreteLogarithm ProblemIlya Mironov Microsoft ResearchAnton Mityagin UCSDKobbi Nissim Ben Gurion University

Speaker: Ramarathnam Venkatesan(Microsoft Research)

Page 2: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

DLP

Discrete Logarithm Problem:

Given gx find x

Believed to be hard in some groups: - Zp

*

- elliptic curves

Page 3: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Hardness of DLP

Hardness of the DLP:– specialized algorithms (index-calculus)

complexity: depends on the algorithm

– generic algorithms (rho, lambda, baby-step giant-step…)

complexity: √p if group has order p

Page 4: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Constrained DLP

Constrained Discrete Logarithm Problem:

Given gx find x, when x S

Example: S consists of exponents with short addition chains.

Page 5: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Hardness of the Constrained DLP

Bad sets (DLP is relatively easy):x with low Hamming weightx [a, b]

{x2 | x < √p}

Good sets (DLP is hard) - ?

Page 6: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Generic Group Model [Nec94,Sho97]

Group G, random encoding σ:GΣ

Group operations oracle:σ(g),σ(h),a,b σ(gahb)

Formally, DLP:given σ(g) and σ(gx), find x

Assume order of g = p is prime

Page 7: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

DLP is hard [Nec94,Sho97]

Suppose there is an algorithm that solves the DLP in the generic group model:1. The algorithm makes n queries

σ(g), σ(gx), σ(ga1x+b1), σ(ga2x+b2),…, σ(ganx+bn)2. The simulator answers randomly but consistently, treating x as a formal variable.3. The algorithm outputs its guess y4. The simulator chooses x at random.5. The simulator loses if there is:

— inconsistency: gaix+bi = gajx+bj for some i, j;— x = y.

Pr < n2/p

Pr = 1/p

Page 8: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

DLP is hard [Nec94,Sho97]

Probability of success of any algorithm for the DLP in the generic group model is at most:

n2/p + 1/p,where n is the number of group operations.

Page 9: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Graphical representation

Queries: σ(g),σ(gx),σ(ga1x+b1),σ(ga2x+b2),…, σ(ganx+bn)

Zp

Zp

0

a1x+b1

a2x+b2

1

x

a3x+b3

x

success

y

Page 10: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Graphical representation

Queries: σ(g),σ(gx),σ(ga1x+b1),σ(ga2x+b2),…, σ(ganx+bn)

Zp

Zp

0

a1x+b1

a2x+b2

1

x

a3x+b3

x

=

failure

y

Page 11: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Attack

The argument is tight:if for some σ(gaix+bi) = σ(gajx+bj), computing x is easy

Page 12: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Constrained DLP

Zp

Zp

0

a1x+b1

a2x+b2

1

x

a3x+b3

given σ(g) and σ(gx), find xS

S

Page 13: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Generic complexity of S

Cα(S) = generic α-complexity of S Zp is the smallest such that their covers an α-fraction of S.

Zp0S

number of linesintersection set

Page 14: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Bound

Adversary who is making at most n queries succeeds in solving DLP: with probability at most

n2/p + 1/p

DLP constrained to set S: If n < Cα(S), probability is at most

α + 1/|S|

Page 15: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

What’s known about Cα(S)?

Obvious: Cα(S) < √ α p (omitting constants)

Cα(S) < α|S|

Cα(S) > √ α|S|

Zp0

Zp

S

Page 16: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Simple bounds

p|S|

√αp

αpCα(S)

log scale √p

sweet spot:small set, high complexity

Page 17: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Random subsets [Sch01]

p|S|

√αp

αpCα(S)

log scale √p

random subsets

Page 18: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Problem

p|S|

√αp

αpCα(S)

log scale √p

random subsetsshort description???

Page 19: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Relaxing the problem: Cbsgs1

Cbsgs1(S) = baby-step-giant-step-1-complexityTwo lists: ga1, ga2,…, gan and gx-b1, gx-b2,…, gx-bn

Zp0

a1

a2

a3

x-b1

x-b2

a1+b2a2+b2a3+b1

Page 20: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Modular weak Sidon set [EN77]

S is such that for any distinct s1,s2,s3,s4S

s1 + s2 ≠ s3 + s4 (mod p)

Zp0

a1

a2

x-b1

x-b2

a1+b2a2+b2a2+b1 a1+b1

all four cannot belong to S

Page 21: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Zarankiewicz bound

a1

b2

b1

a2

a1+b1

a1+b2

a2+b1

a2+b2

How many elements ofS can be in the table?

S is such that for any distinct s1,s2,s3,s4S

s1 + s2 ≠ s3 + s4 (mod p)

Zarankiewicz bound:at most n3/2

Cbsgs1(S) >|S|2/3

Page 22: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Weak modular Sidon sets

S is such that for any distinct s1,s2,s3,s4S

s1 + s2 ≠ s3 + s4 (mod p)

Explicit constructions for such sets exist of size O(p1/2).

Higher order Sidon sets :s1 + s2 + s3 ≠ s4 + s5 + s6 (mod p)

Turan-type bound:Cbsgs1(S) < |S|3/4

Page 23: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

A harder problem: Cbsgs

Cbsgs(S) = baby-step-giant-step-complexityTwo lists: ga1, ga2,…, gan and gс1x-b1,gc2x-b2,…,gcnx-bn

Zp0

a1

a2

a3

c1x-b1c2x-b2

x3 x2 x1 y1 y2 y3

Page 24: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Harder the problem: Cbsgs

S: for any six distinct x1,x2,x3,y1,y2,y3S

(x1-x2)/(x2-x3) ≠ (y1-y2)/(y2-y3) (mod p)

Zp0

a1

a2

a3

c1x-b1c2x-b2

x3 x2 x1 y1 y2 y3

all six cannot belong to S

Page 25: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Zarankiewicz bound

(b1,c1)

a2

a1

How many elements ofS can be in the table?

S: for any six distinct x1,x2,x3,y1,y2,y3S

(x1-x2)/(x2-x3) ≠ (y1-y2)/(y2-y3) (mod p)

Zarankiewicz bound:still at most n3/2

Cbsgs(S) > |S|2/3

(b2,c2)(b3,c3)

x1 x2 x3

y1 y2 y3

Page 26: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

How to construct?

S: for any six distinct x1,x2,x3,y1,y2,y3S

(x1-x2)/(x2-x3) ≠ (y1-y2)/(y2-y3) (mod p)

“Six-wise independent set” of size p1/6

Page 27: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Generic complexity

Zp

l1

“Smallest” possible theorem involves 7 lines:

l2

l3

l4

lx

lylz

x1 y1x2

z1x3

x4y2

y3 z2 y4 z3 z4

Page 28: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Bipartite Menelaus theorem

S: for any twelve distinct x1,x2,x3,x4, y1,y2,y3,y4,z1,z2,z3,z4 S

x1-y1 x1-z1 z1(x1-y1) y1(x1-z1)

x2-y2 x2-z2 z2(x2-y2) y2(x2-z2)

x3-y3 x3-z3 z3(x3-y3) y3(x3-z3)

x4-y4 x4-z4 z4(x4-y4) y4(x4-z4)

det ≠0

degree 6 polynomial

Page 29: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

How to construct?

“12-wise independent set” of size p1/12

C(S) > |S|3/5

Page 30: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Conclusion

p|S|

√αp

αpCα(S)

log scale √p

random subsets

Cbsgs1

Cbsgs

p1/6p1/12

C(αp)1/20(αp)1/9

p1/3

(αp)1/4

Page 31: Hard Instances of the Constrained Discrete Logarithm Problem Ilya MironovMicrosoft Research Anton MityaginUCSD Kobbi NissimBen Gurion University Speaker:

Open problems

Better constructions: - stronger bounds- explicit

Constrained DLP for natural sets:- short addition chains- compressible binary

representation- three-way products xyz