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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)

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

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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